Goods & Services

Downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data in the health, nutrition, wellness, medical, scientific, and pharmaceutical fields; downloadable software for monitoring, tracking, and analyzing health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; downloadable software using artificial intelligence for monitoring, tracking, and analyzing health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; downloadable software for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; downloadable software using artificial intelligence for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; downloadable chatbot software using artificial intelligence for personalized health and medical recommendations, diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, and setting and monitoring individual health goals; downloadable software for accessing and refreshing patient medical records from health information exchanges; downloadable software for data processing and analysis for use with medical clinical trials, research studies, and health management and treatment; downloadable software for clinical trial data collection, storage, and analysis; downloadable software using artificial intelligence for identifying and enrolling in clinical trials and eligible research opportunities based on patient medical history and individual health status; downloadable software to support treatment between a patient and provider, namely, software for sharing patient files and healthcare data; downloadable software using artificial intelligence for the capture and analysis of health data to improve patient care; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable software for using surgical equipment, namely, software for operating, controlling, monitoring, and analyzing and processing data from surgical equipment; downloadable video files in the fields of health, nutrition, wellness, medicine, scientific, and pharmaceuticals; downloadable printable educational materials in the fields of health, nutrition, wellness, medicine, scientific, and pharmaceuticals; downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable computer software for application and database integration. Wearable medical technological devices for the detection, monitoring, and management of biomarkers and health and physiological data, namely, wearable activity and biometric data trackers, wearable monitors and medical apparatus and instruments for monitoring vital signs, blood properties and respiratory properties and events; all the foregoing for medical use. Printed publications, namely, brochures, journals, reports, newsletters, booklets, magazines and teaching materials in the fields of health, nutrition, medicine, science, pharmaceuticals, and technology. Promoting public interest and awareness of issues, developments, and topics in the fields of health, nutrition, medicine, science, pharmaceuticals, and technology; data processing services in the field of healthcare; health care cost management and review services; managed care services, namely, electronic processing of healthcare information; updating and maintenance of information in registries; patient relationship management services. Telecommunication services, namely, transmission of voice, data, graphics, images, audio and video by means of telecommunications networks, wireless communication networks, and the internet; transmission of voice, data, graphics, images, audio and video related to health by means of telecommunications networks, wireless communication networks, and the Internet via a telecommunications platform; electronic transmission of messages and data; transmission of information by electronic communications networks; providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data. Online publication of and providing non-downloadable publications in the nature of articles and presentations in the fields of health, nutrition, wellness, medicine, science, and pharmaceuticals via a website; providing non-downloadable educational videos in the fields of health, nutrition, wellness, medicine, science, and pharmaceuticals via a website; providing online non-downloadable educational videos in the fields of health, nutrition, wellness, medicine, science, and pharmaceuticals; online personal coaching services in the fields of health, nutrition, wellness, medicine, science, and pharmaceuticals. Software as a service (SAAS) featuring software for collecting, processing, analyzing, transmitting, validating and displaying data in the health, nutrition, wellness, medical, scientific, and pharmaceutical fields; software as a service (SAAS) featuring software for monitoring, tracking, and analyzing health, medical, genetic, movement, nutritional, wellness, geographic, health risk, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; software as a service (SAAS) featuring software using artificial intelligence (AI) for monitoring, tracking, and analyzing health, medical, genetic, movement, nutritional, wellness, geographic, health risk, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; software as a service (SAAS) featuring software for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; software as a service (SAAS) featuring software using artificial intelligence (AI) for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; providing temporary use of online non-downloadable chatbot software using artificial intelligence (AI) for personalized health and medical recommendations, diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, and setting and monitoring individual health goals; software as a service (SAAS) featuring software for accessing and refreshing patient medical records from health information exchanges; software as a service (SAAS) featuring software for data processing and analysis for use with medical clinical trials, research studies, and health management and treatment; software as a service (SAAS) featuring software for clinical trial data collection, storage, and analysis; software as a service (SAAS) featuring software using artificial intelligence (AI) for identifying and enrolling in clinical trials and eligible research opportunities based on patient medical history and individual health status; software as a service (SAAS) featuring software for supporting treatment between a patient and provider, namely, software for sharing patient files and healthcare data; software as a service (SAAS) featuring software using artificial intelligence (AI) for the capture and analysis of health data to improve patient care; software as a service (SAAS) featuring software using artificial intelligence (AI) for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; software as a service (SAAS) featuring software using artificial intelligence (AI) for patient case management for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; software as a service (SAAS) featuring software for using surgical equipment; software as a service (SAAS) featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields; application service provider featuring application programming interface (API) software; providing online non-downloadable software that enables users to enter, access, track, monitor and generate health and medical information and reports via an interactive website; medical research. Providing information about health and the management of health conditions; healthcare advisory services; healthcare services in the nature of real time medical diagnosis support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks; providing personalized healthcare and medical information in the fields of mental health, physical health, nutrition, wellness, diet and exercise, symptom, disease, and treatment management; providing personalized healthcare and medical information for use in optimizing the use of medication for health and wellness treatments by offering data featuring health, medical, genetic, movement, nutritional, wellness, geographic, health risk, and demographic information; medical services in the nature of providing health data analytics and care delivery data analytics and insights to patients, doctors, hospitals, and medical professionals for diagnostic and treatment purposes from a database; medical diagnostic testing, monitoring, and reporting services; medical testing and analysis for diagnostic and population health purposes provided by medical laboratories in the fields of oncology and virology; medical services, namely, screening, diagnosing or grading the severity of a disease or health condition based on image data; medical analysis services for diagnostic and treatment purposes provided by medical laboratories.

Abstract

A user-interface for visualizing a colonoscopy procedure includes a video region, a polyp annotation and identification graphic, and a lost polyp navigational aid. A live video feed received from a colonoscope is displayed in the video region. The polyp annotation depicts a location of a polyp within a colon and is presented on the live video feed. When the polyp is lost from the field of view (e.g., as a result of surgical tool insertion), the lost polyp navigation aid displays directions and/or signals to guide the endoscopist back to the lost polyp.

IPC Classes  ?

• A61B 1/31 - Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopesIlluminating arrangements therefor for the rectum, e.g. proctoscopes, sigmoidoscopes
• A61B 1/00 - Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopesIlluminating arrangements therefor
• G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods

Abstract

In one aspect, a field emission source is disclosed herein. The field emission source may include a field emission layer having at least one structure configured to emit electrons, a spacer contacting the field emission layer, and a window layer contacting the spacer and positioned opposed the at least one structure. The window layer may be transparent to electrons. Moreover, the field emission layer, the spacer, and the window layer may form an airtight cavity. In some cases, the field emission source may be used in an ion mobility spectrometer (IMS) system.

IPC Classes  ?

• G01N 27/622 - Ion mobility spectrometry
• H01J 3/02 - Electron guns

Abstract

Introduced here is an ingestible device (that is able to deliver medication directly into tissue along the gastrointestinal tract. Administration of a medication stored in the ingestible device may require that the ingestible device orient itself against the tissue. To accomplish this, the ingestible device may have an asymmetrically weighted formfactor. For example, the ingestible device may be weighted along an end (also called the “weighted end”) through which the needle extends in order to promote self-orientation.

IPC Classes  ?

• A61M 31/00 - Devices for introducing or retaining media, e.g. remedies, in cavities of the body

Goods & Services

Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Telecommunications access services; telecommunication services provided via Internet platforms in the field of health; providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. Research services in the field of data analytics and machine learning, namely analysis of technical data relating to clinical trials, laboratory and genomics; data mining; scientific research and machine software and artificial intelligence programming and technology consulting in the fields of drug development, personalized medicine and patient care pathways; artificial intelligence as a service (AIaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SaaS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields; providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways. Healthcare services, namely, medical counseling services and treatment monitoring using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultation rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks.

Abstract

Introduced here is a system that is able to extract metadata from documents using LLMs. At a high level, the system obtains a file relating to a clinical trial. The system applies, to the file, a hash function to produce a hash value. Then, the system compares the hash value against hash values representing previously uploaded files to determine whether a matching hash value exists. In response to determining that no matching hash value exists, the system extracts an identifier for the clinical trial by applying an LLM to metadata of the file. The system then compares the identifier against identifiers of clinical trials to determine whether a matching identifier exists. Finally, in response to determining that no matching identifier exists, the generative platform prompts the user for information regarding the clinical trial.

IPC Classes  ?

• G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
• G06F 40/10 - Text processing
• G06F 40/30 - Semantic analysis
• G06F 40/40 - Processing or translation of natural language
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

Introduced here are approaches to generating an image with a fundus camera based on parameters determined through modeling of eye motion. The method captures a series of images to generate pupil position data over time. Using this data, the method determines a model for estimating pupil positions and predicts a time associated with a minimum pupil velocity. The method can estimate the pupil position at this time and generate a fundus camera configuration based on the position. The method can transmit a command to capture an image of the eye using the fundus camera configuration. By implementing these approaches, an imaging system can improve the quality of retinal imaging for patients with eye motion.

IPC Classes  ?

• A61B 3/14 - Arrangements specially adapted for eye photography
• A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• A61B 3/13 - Ophthalmic microscopes
• A61B 5/16 - Devices for psychotechnicsTesting reaction times
• G01N 15/1434 - Optical arrangements
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes

Abstract

A modular system can be used with commercial eyeglasses to interface with an electronic eye-mounted ocular device and used to control and/or actuate the electronic eye-mounted ocular device, exchange data with the electronic eye-mounted ocular device, and/or charge the electronic eye-mounted ocular device. The modular system includes an electroactive stick-on component attachable to a portion of an eyeglasses lens; and an electronic system attachable to an eyeglass frame in electrical communication with the electroactive stick-on component.

IPC Classes  ?

• G02C 11/00 - Non-optical adjunctsAttachment thereof
• G02C 7/04 - Contact lenses for the eyes

Goods & Services

Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Telecommunications services; telecommunications platform related to health (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. Providing data analytics and machine learning services, namely analyzing and organizing clinical, laboratory and genomic data, data mining, scientific research and machine software and artificial intelligence programing and consulting in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SAAS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Healthcare services in the nature of real time support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the Internet or telecommunication networks.

Goods & Services

Downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data in the health, nutrition, wellness, medical, scientific, and pharmaceutical fields; downloadable software using artificial intelligence for monitoring, tracking, and analyzing health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; downloadable software using artificial intelligence for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; downloadable chatbot software using artificial intelligence for personalized health and medical recommendations, diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, and setting and monitoring individual health goals; downloadable software for accessing and refreshing patient medical records from health information exchanges; downloadable software using artificial intelligence for identifying and enrolling in clinical trials and eligible research opportunities based on patient medical history and individual health status; downloadable software for clinical trial data collection, storage, and analysis; downloadable software using artificial intelligence for the capture and analysis of health data to improve patient care. Providing online non-downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data in the health, nutrition, wellness, medical, scientific, and pharmaceutical fields; providing online non-downloadable software using artificial intelligence for monitoring, tracking, and analyzing health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; providing online non-downloadable software for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; providing temporary use of online non-downloadable chatbot software using artificial intelligence for personalized health and medical recommendations, diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, and setting and monitoring individual health goals; providing online non-downloadable software for accessing and refreshing patient medical records from health information exchanges; providing online non-downloadable software using artificial intelligence for identifying and enrolling in clinical trials and eligible research opportunities based on patient medical history and individual health status; providing online non-downloadable software for clinical trial data collection, storage and analysis; providing online non-downloadable software using artificial intelligence for the capture and analysis of health data to improve patient care. Providing information about health and the management of health conditions; healthcare advisory services; healthcare services in the nature of real time medical diagnosis support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks; providing personalized healthcare and medical information in the fields of mental health, physical health, nutrition, wellness, diet and exercise, symptom, disease, and treatment management; providing personalized healthcare and medical information for use in optimizing the use of medication for health and wellness treatments by offering data featuring health, medical, genetic, movement, nutritional, wellness, geographic, health risk, and demographic information; medical services in the nature of providing a database featuring health data analytics and care delivery data analytics and insights to patients, doctors, hospitals, and medical professionals for diagnostic and treatment purposes (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); medical diagnostic testing, monitoring, and reporting services; laboratory testing and analysis for diagnostic and population health purposes in the fields of oncology and virology; medical services, namely, screening, diagnosing or grading the severity of a disease or health condition based on image data; medical analysis services for diagnostic and treatment purposes provided by medical laboratories.

Goods & Services

Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Telecommunications services; telecommunications platform related to health (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. Providing data analytics and machine learning services, namely analyzing and organizing clinical, laboratory and genomic data, data mining, scientific research and machine software and artificial intelligence programing and consulting in the fields of drug development, personalized medicine and patient care pathways (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SAAS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Healthcare services in the nature of real time support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the Internet or telecommunication networks.

Goods & Services

Downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Telecommunications services; telecommunications platform related to health (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. Providing temporary use of on-line non-downloadable software and programs using artificial intelligence (AI) for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; providing online non-downloadable software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific, and pharmaceutical fields; providing data analytics and machine learning services, namely analyzing and organizing clinical, laboratory and genomic data, data mining, scientific research and machine software and artificial intelligence programing and consulting in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SAAS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Healthcare services in the nature of real time support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the Internet or telecommunication networks.

Goods & Services

Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Telecommunications access services; telecommunication services provided via Internet platforms in the field of health; providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. Research services in the field of data analytics and machine learning, namely analysis of technical data relating to clinical trials, laboratory and genomics; data mining; scientific research and machine software and artificial intelligence programming and technology consulting in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; artificial intelligence as a service (AIaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SaaS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. Healthcare services, namely, medical counseling services and treatment monitoring using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks.

Abstract

Devices, systems, and methods for passively regulating or controlling Intraocular Pressure (IOP) are provided. A device may be configured to be implanted or attached to a patient’s eye to provide regulated drainage of aqueous humor (AH) out of the eye to an exterior of the eye. The device may include a housing comprising an inlet and an outlet, and a pressure relief valve coupled to the housing. The pressure relief valve may be configured to open to allow passage of the aqueous humor from an ingress of the pressure relief valve to an egress of the pressure relief valve in response to a pressure of the aqueous humor on the ingress exceeding a threshold. The device may include a filter configured to allow passage of fluid from the egress through the outlet along a fluid path extending from the inlet to the outlet.

IPC Classes  ?

• A61F 9/007 - Methods or devices for eye surgery
• A61N 1/36 - Applying electric currents by contact electrodes alternating or intermittent currents for stimulation, e.g. heart pace-makers
• A61N 1/372 - Arrangements in connection with the implantation of stimulators
• A61N 1/375 - Constructional arrangements, e.g. casings

Abstract

A platform for dynamically generating a visual scheme of a graphical user interface to indicate compliance with study requirements is disclosed herein. The platform can receive device data corresponding to a first time period. The platform can generate a first compliance indicator associated with a first data type of the device data. The platform can generate a second compliance indicator associated with a second data type of the device data. The platform can generate a third compliance indicator associated with a third data type of the device data. The platform can generate an overall compliance indicator based on the first, second, and third compliance indicators. The platform can generate a first visual representation of the overall compliance indicator in a first color or in a second color based on the value of the overall compliance indicator.

IPC Classes  ?

• G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
• G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation

Abstract

Introduced here are diabetes management platforms able to examine glucose measurements associated with a subject to discover patterns indicative of similar behaviors/circumstances. More specifically, a diabetes management platform can acquire multiple data series generated by a glucose monitoring device that monitors the blood glucose level of an individual over multiple time intervals. The diabetes management platform can then apply a similarity algorithm to produce a distance measure (also referred to as a “similarity measure”) for each data series. For example, the diabetes management platform may, for each data series, perform dynamic time warping to produce a distance measure with respect to each of the other data series. The diabetes management platform can identify patterns indicative of similar behaviors/circumstances based on these distance measures.

IPC Classes  ?

• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G09B 5/02 - Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip
• G09B 19/00 - Teaching not covered by other main groups of this subclass
• G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

A method of monitoring an internal body temperature of a patient includes detecting a skin temperature of the patient using a temperature sensor in a body-mountable temperature monitor attached to the patient; calculating, using the temperature sensor, a heat flux associated with the body-mountable temperature monitor based on selectively activating a heater in the body-mountable temperature monitor; and determining the internal body temperature of the patient using the skin temperature and the heat flux.

IPC Classes  ?

• G01K 13/20 - Clinical contact thermometers for use with humans or animals
• G01K 1/14 - SupportsFastening devicesArrangements for mounting thermometers in particular locations
• G01K 1/143 - SupportsFastening devicesArrangements for mounting thermometers in particular locations for measuring surface temperatures
• G01K 1/20 - Compensating for effects of temperature changes other than those to be measured, e.g. changes in ambient temperature
• G01K 7/22 - Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat using resistive elements the element being a non-linear resistance, e.g. thermistor

Abstract

Introduced here is an approach for training machine learning models to generate combined measures to detect disease progression. Methods and systems discussed herein generate combined measures in a supervised or unsupervised manner using single measures derived from higher-frequency, longitudinal free-living data (or simply "free-living data") or lower-frequency, controlled-setting data, such as virtual motor exam (VME) data or gait analysis data. By generating combined measures, these models can more accurately detect disease progression, capturing a more comprehensive view of the patient's condition.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A technique for monitoring data quality during a research study or from a care setting using body wearable monitors includes storing sensor data, received from the body wearable monitors worn by participants in the research study, into a database. Data quality metrics for the sensor data are derived by determining whether the sensor data falls within specified value ranges. The sensor data stored within the database is annotated with the data quality metrics. Data quality decisions for the sensor data are generated based on data quality rules specified for the research study and applied to the sensor data and the data quality metrics. The data quality decisions are monitored in real-time or on a periodic schedule and a data quality alert is issued when one or more of the data quality decisions falls outside of an acceptable limit specified for the research study.

IPC Classes  ?

• G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
• G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation

Abstract

Introduced here are health management platforms able to infer the health state of a subject based on behavioral changes reflected in the digital activities performed by a subject. A health management platform can initially acquire contextual data pertaining to digital activities performed by the subject. The health management platform can identify the target(s) of the digital activities by parsing the contextual data, and then compile the digital activities and corresponding activities into a personalized valence index. Thereafter, the health management platform can compare digital activities performed by the subject to the entries included in the personalized valence index. If a matching entry is not discovered, the health management platform can identify an instance of behavior change. These instances of behavior change may be indicative of changes in the subject's health state.

IPC Classes  ?

• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G06F 16/951 - IndexingWeb crawling techniques
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Introduced here are health management platforms able to infer the health state of a subject based on behavioral changes reflected in the digital activities performed by a subject. A health management platform can initially acquire contextual data pertaining to digital activities performed by the subject. The health management platform can identify the target(s) of the digital activities by parsing the contextual data, and then compile the digital activities and corresponding activities into a personalized valence index. Thereafter, the health management platform can compare digital activities performed by the subject to the entries included in the personalized valence index. If a matching entry is not discovered, the health management platform can identify an instance of behavior change. These instances of behavior change may be indicative of changes in the subject's health state.

IPC Classes  ?

• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G06F 16/951 - IndexingWeb crawling techniques
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Goods & Services

(1) Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (1) Telecommunications access services; telecommunication services provided via Internet platforms in the field of health; providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. (2) Research services in the field of data analytics and machine learning, namely analysis of technical data relating to clinical trials, laboratory and genomics; data mining; scientific research and machine software and artificial intelligence programming and technology consulting in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; artificial intelligence as a service (AIaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SaaS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (3) Healthcare services, namely, medical counseling services and treatment monitoring using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks.

Goods & Services

(1) Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (1) Telecommunications access services; telecommunication services provided via Internet platforms in the field of health; providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. (2) Research services in the field of data analytics and machine learning, namely analysis of technical data relating to clinical trials, laboratory and genomics; data mining; scientific research and machine software and artificial intelligence programming and technology consulting in the fields of drug development, personalized medicine and patient care pathways; artificial intelligence as a service (AIaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SaaS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SaaS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields; providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways. (3) Healthcare services, namely, medical counseling services and treatment monitoring using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultation rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks.

Abstract

Introduced here is a method, a system, a device, etc. for displaying health-related data (e.g., blood glucose measurements) relevant to user's selection. The method, the system, the device, etc. can be based on: receiving healthcare-related data from data streams associated with a profile of a patient; identifying, based on a least a subset of the data streams, a time window corresponding to a contextual event indicative of a patient activity that has a potential of affecting metabolism of the patient; determining a graphical representation of the contextual event; generating a graph of blood glucose level over time for display; detecting a user indication of a user interest in a time point along the graph of the blood glucose level; and highlighting the graphical representation of the contextual event in response to the time point falling within the identified time window.

IPC Classes  ?

• G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
• G06F 9/451 - Execution arrangements for user interfaces
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G16H 20/60 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
• G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Abstract

A subject interface including bellows for a retinal imaging system and a retinal imaging are described. In an embodiment, the subject interface comprises a headrest shaped to couple with a forehead of a subject, the headrest comprising a rim defining a headrest aperture; and a bellows comprising an outer circumference coupled to the rim; and an inner circumference defining a bellows aperture overlapping with the headrest aperture. In an embodiment, the bellows is configured to move the inner circumference relative to the outer circumference through deformation of the bellows. In an embodiment, the inner circumference is configured to move relative to the outer circumference to displace the bellows aperture primary axis relative to the headrest aperture primary axis. In an embodiment, the bellows defines one or more waves, shaped to unfold as the bellows aperture primary axis is displaced relative to the headrest primary axis.

IPC Classes  ?

• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• A61B 3/14 - Arrangements specially adapted for eye photography

Abstract

Methods and systems of analyzing and displaying medical videos are described herein. In some embodiments, the methods and systems may be used during an endoscopy procedure using a multi-camera endoscope having a first camera and a second camera. A method according to the present disclosure may include: receiving a first medical video from a first camera; receiving a second medical video from a second camera; detecting one or more target features of the second medical video using a pre-trained target feature detector comprising a neural network; generating an alert indicating the detection of the one or more target features in the second medical video; and displaying the first medical video and the alert on a display.

IPC Classes  ?

• A61B 1/00 - Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopesIlluminating arrangements therefor
• A61B 1/04 - Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopesIlluminating arrangements therefor combined with photographic or television appliances
• A61B 1/31 - Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopesIlluminating arrangements therefor for the rectum, e.g. proctoscopes, sigmoidoscopes

Goods & Services

(1) Downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data in the health, nutrition, wellness, medical, scientific, and pharmaceutical fields; downloadable software using artificial intelligence for monitoring, tracking, and analyzing health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; downloadable software using artificial intelligence for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; downloadable chatbot software using artificial intelligence for personalized health and medical recommendations, diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, and setting and monitoring individual health goals; downloadable software for accessing and refreshing patient medical records from health information exchanges; downloadable software using artificial intelligence for identifying and enrolling in clinical trials and eligible research opportunities based on patient medical history and individual health status; downloadable software for clinical trial data collection, storage, and analysis; downloadable software using artificial intelligence for the capture and analysis of health data to improve patient care. (1) Providing online non-downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data in the health, nutrition, wellness, medical, scientific, and pharmaceutical fields; providing online non-downloadable software using artificial intelligence for monitoring, tracking, and analyzing health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data, and demographic data for use in connection with clinical trials, research studies, and health management and treatment; providing online non-downloadable software for diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, appointment scheduling, and setting and monitoring individual health goals; providing temporary use of online non-downloadable chatbot software using artificial intelligence for personalized health and medical recommendations, diet and exercise planning, mental health support, symptom evaluation, medication optimization, personalized health insights, disease and treatment management, vaccination tracking, and setting and monitoring individual health goals; providing online non-downloadable software for accessing and refreshing patient medical records from health information exchanges; providing online non-downloadable software using artificial intelligence for identifying and enrolling in clinical trials and eligible research opportunities based on patient medical history and individual health status; providing online non-downloadable software for clinical trial data collection, storage and analysis; providing online non-downloadable software using artificial intelligence for the capture and analysis of health data to improve patient care. (2) Providing information about health and the management of health conditions; healthcare advisory services; healthcare services in the nature of real time medical diagnosis support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the internet or telecommunication networks; providing personalized healthcare and medical information in the fields of mental health, physical health, nutrition, wellness, diet and exercise, symptom, disease, and treatment management; providing personalized healthcare and medical information for use in optimizing the use of medication for health and wellness treatments by offering data featuring health, medical, genetic, movement, nutritional, wellness, geographic, health risk, and demographic information; medical services in the nature of providing a database featuring health data analytics and care delivery data analytics and insights to patients, doctors, hospitals, and medical professionals for diagnostic and treatment purposes (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); medical diagnostic testing, monitoring, and reporting services; laboratory testing and analysis for diagnostic and population health purposes in the fields of oncology and virology; medical services, namely, screening, diagnosing or grading the severity of a disease or health condition based on image data; medical analysis services for diagnostic and treatment purposes provided by medical laboratories.

Goods & Services

(1) Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (1) Telecommunications services; telecommunications platform related to health (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. (2) Providing data analytics and machine learning services, namely analyzing and organizing clinical, laboratory and genomic data, data mining, scientific research and machine software and artificial intelligence programing and consulting in the fields of drug development, personalized medicine and patient care pathways (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SAAS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (3) Healthcare services in the nature of real time support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the Internet or telecommunication networks.

Goods & Services

(1) Downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (1) Telecommunications services; telecommunications platform related to health (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. (2) Providing temporary use of on-line non-downloadable software and programs using artificial intelligence (AI) for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; providing online non-downloadable software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific, and pharmaceutical fields; providing data analytics and machine learning services, namely analyzing and organizing clinical, laboratory and genomic data, data mining, scientific research and machine software and artificial intelligence programing and consulting in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SAAS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (3) Healthcare services in the nature of real time support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the Internet or telecommunication networks.

Goods & Services

(1) Downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; downloadable software for collecting, processing, analyzing, transmitting, validating and displaying data using artificial intelligence in the health, medical, scientific and pharmaceutical fields; downloadable software for data analytics using artificial intelligence in the fields of drug discovery, personalized medicine and patient care pathways; downloadable computer software using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; downloadable software for patient case management using artificial intelligence for viewing and sharing patient health information, performing healthcare data analytics, generating patient insights, and managing patient care; downloadable application programming interface (API) software; downloadable computer software for use as an application programming interface (API); downloadable software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (1) Telecommunications services; telecommunications platform related to health (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to databases; providing access to databases featuring patient health data; providing access to databases featuring medical research data; providing access to databases featuring clinical trial data; providing access to databases featuring health data, medical data, genetic data, movement data, nutritional data, wellness data, geographic data, health risk data and demographic data. (2) Providing data analytics and machine learning services, namely analyzing and organizing clinical, laboratory and genomic data, data mining, scientific research and machine software and artificial intelligence programing and consulting in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software for data analytics in the fields of drug discovery, personalized medicine and patient care pathways; artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for collecting, processing, analyzing, transmitting, validating and displaying data in the health, medical, scientific and pharmaceutical fields; software as a service (SAAS) services featuring software using artificial intelligence (AI) for data analytics and machine learning in the fields of drug development, personalized medicine and patient care pathways; application service provider featuring application programming interface (API) software; software as a service (SAAS) services featuring software for identity and authorization management in the health, medical, scientific and pharmaceutical fields. (3) Healthcare services in the nature of real time support services, health recommendations using artificial intelligence, and treatment tracking using artificial intelligence, algorithm-based machine learning, and analysis technologies; medical advisory services; medical counseling; medical services; healthcare; providing healthcare information; online medical consultations rendered in virtual environments; provision of health care and medical services by health care professionals via the Internet or telecommunication networks.

Abstract

Introduced here are retinal cameras having one or more optical components whose position can be modified so that the left and right eyes can be imaged during a single imaging operation. Collectively, the optical component(s) may be referred to as an “optical assembly.” An optical assembly can include the objective lens, lens tube, and other optical components such as mirror(s), light source(s), capturing medium(s), etc. An optical assembly of a retinal camera may be movable between a first position and a second position along an arcuate path. By moving the optical assembly between the first and second positions along the arcuate path, the retinal camera can align the lens tube with the left and right eyes of an individual while clearing her nose. Thus, the retinal camera may generate images of the left and right eyes during an imaging procedure without requiring that the individual move her head.

IPC Classes  ?

• A61B 3/15 - Arrangements specially adapted for eye photography with means for aligning, spacing or blocking spurious reflection
• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes

Abstract

Introduced here are diabetes management platforms able to make annotations to physiological data of a subject whose glycemic health state is being monitored. These annotations can be used to classify excursions detected in the physiological data to facilitate the identification of a therapeutic behavior change intended to improve the glycemic health state of the subject. For example, a health coach may review the annotation(s) associated with the subject before generating a recommendation for improving the glycemic health state. As another example, the diabetes management platform can automatically identify an appropriate recommendation based on the annotation(s).

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation

Abstract

The sleep staging platform disclosed herein enables accurate sleep stage classification by combining actigraphy data with heart rate data. The platform may use a multi-model approach that includes a first machine learning model to evaluate sleep stages using heart rate patterns from polysomnography datasets related to a wearable device. The platform may combine the outputs of the heart rate-based model with actigraphy features into a second model to further evaluate sleep stages. The platform may segment events based on timestamps to detect sleep stages and calculate clinically relevant sleep metrics such as total sleep time and wake after sleep onset. By using a multi-model approach, the platform reduces feature dimensionality, enabling practical training with small polysomnography datasets related to wearable devices. The combination of heart rate patterns and actigraphy features may enhance sleep staging accuracy, particularly when heart rate data is derived from motion-sensitive polysomnography signals.

IPC Classes  ?

• A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

Introduced here are approaches to ensuring that digital images generated during diagnostic sessions are properly associated with the appropriate patients. By implementing these approaches, a diagnostic platform can minimize the time needed to manually input information prior to a diagnostic session and improve the accuracy of this information.

IPC Classes  ?

• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes
• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• A61B 3/14 - Arrangements specially adapted for eye photography
• G06V 40/14 - Vascular patterns
• G06V 40/18 - Eye characteristics, e.g. of the iris
• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS

Abstract

A model eye for evaluating a retinal imaging system includes a retinal cup and a resolution target. The retinal cup includes an interior surface having a bowl-like shape to represent a fundus of a human eye. The resolution target is disposed on the interior surface for assessing a spatial resolution of the retinal imaging system. The resolution target includes light and dark contrasting regions with straight edges separating the light and dark contrasting regions. At least two of the straight edges are orthogonal. An array of dark color microfeatures may be disposed in the light contrasting region and an array of light color microfeatures may be disposed in the dark contrasting region. The light and dark color microfeatures are variably sized for assessing the spatial resolution of the retinal imaging system.

IPC Classes  ?

• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes
• A61B 3/14 - Arrangements specially adapted for eye photography
• G09B 23/30 - Anatomical models

Abstract

A technique of estimating a continuous heart rate of a subject includes acquiring pulsatility data indicative of a cardiac cycle of the subject and motion data indicative of a motion of the subject. Frequency transformations are performed on the pulsatility and motion data over discrete windows of temporal length T to generate a set of windowed spectra. The discrete windows are temporally overlapping and each temporally offset from one another. Heart rate values, each corresponding to one of the windowed spectra, are output using a processing pipeline including one or more neural networks trained to collectively output one of the heart rate values for each windowed spectra. The continuous heart rate is estimated based upon a set of the heart rate values from the discrete windows that are temporally overlapping.

IPC Classes  ?

• A61B 5/024 - Measuring pulse rate or heart rate
• G06N 3/044 - Recurrent networks, e.g. Hopfield networks
• G06N 3/045 - Combinations of networks
• G06N 3/0464 - Convolutional networks [CNN, ConvNet]
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

In some embodiments, a computer-implemented method of measuring heart rate analytics using raw photoplethysmography (PPG) data is provided. A computing system determines a plurality of frequency peaks in the raw PPG data using a Fourier analysis. The computing system determines a plurality of selected frequency peaks from the plurality of frequency peaks. For each selected frequency peak of the plurality of selected frequency peaks, the computing system creates filtered PPG data by applying a frequency of the selected frequency peak as a high-pass filter to the raw PPG data; detects diastole peaks and systole valleys in the filtered PPG data; and performs one or more pulse quality checks on the detected diastole peaks and systole valleys. The computing system uses diastole peaks and systole valleys associated with a lowest selected frequency peak that passed the pulse quality checks to determine a heart rate analytic measurement.

IPC Classes  ?

• A61B 5/024 - Measuring pulse rate or heart rate
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

Systems and methods for analyzing a blood volume signal are described. In an example, the method comprises extracting self-normalized features from blood volume signals within a signal window; generating a signal quality prediction based on the self-normalized features to provide a quality prediction score, wherein the quality prediction score is between an upper bound and a lower bound; and generating a health metric score based on the blood volume signals in the signal window if the quality prediction score is above a predetermined threshold. In an example, the blood volume signals are photoplethysmography (PPG) signals. In an example, the method includes identifying a signal quality issue if the quality prediction score is below the predetermined threshold.

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• A61B 5/024 - Measuring pulse rate or heart rate
• A61B 5/0295 - Measuring blood flow using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
• A61B 5/08 - Measuring devices for evaluating the respiratory organs
• A61B 5/1455 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value using optical sensors, e.g. spectral photometrical oximeters

Abstract

Systems, methods and devices for physiological signal conversion, classification and diagnosis of medical conditions, and visualization are presented herein. In one embodiment, a method of determining one or more medical conditions based on a physiological signal of a first type is presented. The method includes providing the physiological signal of the first type to a generative model. The method may further include generating, by the generative model, a plurality of physiological signals of a second type from the physiological signal of the first type. The method may further include generating a plurality of classification scores in one-to-one correspondence with the plurality of physiological signals of the second type. The method may further include determining whether a medical condition exists based on the plurality of classification scores.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• A61B 5/318 - Heart-related electrical modalities, e.g. electrocardiography [ECG]
• A61B 5/327 - Generation of artificial ECG signals based on measured signals, e.g. to compensate for missing leads
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/024 - Measuring pulse rate or heart rate

Abstract

In some embodiments, a computer-implemented method of detecting rest states and active states using motion sensor data from a wearable motion sensor is provided. A computing system calculates features based on the motion sensor data. The motion sensor data includes a plurality of axes of motion sensor data. Calculating the features based on the motion sensor data includes calculating correlations between the axes of the plurality of axes of motion sensor data. The computing system calculates entropy of the features, and determines the rest states and the active states based on the entropy of the features.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb

IPC Classes  ?

• A61B 34/20 - Surgical navigation systemsDevices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• G06F 16/738 - Presentation of query results
• G06V 20/40 - ScenesScene-specific elements in video content
• G11B 27/10 - IndexingAddressingTiming or synchronisingMeasuring tape travel
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Introduced here are retinal cameras having optical stops whose size and/or position can be modified to increase the size of the space in which an eye can move while being imaged. In some embodiments, an optical stop is mechanically moved to recover retinal image quality as the subject shifts their eye. In some embodiments, an optical stop is digitally created using a pixelated liquid crystal display (LCD) layer having multiple pixels that are individually controllably. In some embodiments, multiple non-pixelated LCD layers are connected to one another to form a variable transmission stack, and each LCD layer within the variable transmission stack may be offset from the other LCD layers. In such embodiments, the optical stop can be moved by changing which LCD layer is active at a given point in time.

IPC Classes  ?

• A61B 3/14 - Arrangements specially adapted for eye photography
• A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• G02F 1/1334 - Constructional arrangements based on polymer-dispersed liquid crystals, e.g. microencapsulated liquid crystals

Abstract

A method for performing a visual field test that includes presenting, through a set of light emitters within a visual field test area, a first sequence of light stimuli; receiving, responsive to each light stimulus, a user response; and generating a sensitivity map of a visual field of a user as output of a machine learning (ML) model responsive to the user responses as input. The method includes determining that a subset of emitters are to present a second sequence of light stimuli based on the first predicted sensitivity map; presenting, through the subset of emitters, the second sequence of light stimuli; receiving, responsive to each light stimulus, the user response; and generating a second sensitivity map (e.g., by updating the first sensitivity map) as output of the ML model responsive to the user responses to the first and second sequence of light stimuli as input into the ML model.

IPC Classes  ?

• A61B 3/024 - Subjective types, i.e. testing apparatus requiring the active assistance of the patient for determining the visual field, e.g. perimeter types

Abstract

Introduced here is an interactive digital health system (or simply “interactive system”) that is able to update a knowledge base used to facilitate semi-automated conversations to account for feedback. The interactive system can include a collection of modules that, in operation, can provide or support coaching services in the digital health domain, Upon receiving input indicative of a question from a patient, these modules allow the interactive system to perform language modeling to identify content objects in a knowledge base that are relevant to the question. Moreover, the interactive system may update the knowledge base to account for feedback, thereby making the knowledge base more robust to a broad range of questions.

IPC Classes  ?

• G06F 16/2453 - Query optimisation
• G06F 16/2457 - Query processing with adaptation to user needs

Abstract

An eye examination apparatus comprising: a virtual reality device (104) configured to be worn on a user's head (102), the virtual reality device having a housing (203) containing a lens (208) and a display (214) operable to display an image (216) to an eye (202) of the user; and a long-pass filter (204) arranged between the lens (208) and the eye (202) for examining the eye's ability to see the image (216), the long-pass filter (204) having a first transmission region (226) that transmits a visible light (218) and a near-infrared light (220) to the eye (202) and a second transmission region (228) that transmits the near-infrared light (220) and blocks the visible light (218).

IPC Classes  ?

• A61B 3/032 - Devices for presenting test symbols or characters, e.g. test chart projectors
• A61B 3/10 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions
• A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement

Abstract

One aspect of the disclosure here is a virtual reality headset-based system that performs a vision test or eye examination (exam) in an automated and repeatable manner that quantifies the tested user's degree of, or likelihood of suffering from, a stage of Thyroid Eye Disease, TED. The system may be configured to analyze images of the user's eyes to determine various quantifiable metrics, where these metrics can be used to, for example, determine how the management of the disease is progressing. Other aspects are also described.

IPC Classes  ?

• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes
• A61B 3/028 - Subjective types, i.e. testing apparatus requiring the active assistance of the patient for testing visual acuitySubjective types, i.e. testing apparatus requiring the active assistance of the patient for determination of refraction, e.g. phoropters
• A61B 3/11 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring interpupillary distance or diameter of pupils
• A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
• A61B 3/14 - Arrangements specially adapted for eye photography
• G02B 27/01 - Head-up displays
• G06T 19/00 - Manipulating 3D models or images for computer graphics

Abstract

An eye examination apparatus comprising: a virtual reality device configured to be worn on a user's head, the virtual reality device having a housing and a display operable to display a fixation point to an eye of the user that corresponds to any one of a number of diagnostic gaze positions; and an imaging device coupled to the housing that is operable to capture an image of the eye viewing the fixation point for use in examining the eye for an ocular condition.

IPC Classes  ?

• A61B 3/08 - Subjective types, i.e. testing apparatus requiring the active assistance of the patient for testing binocular or stereoscopic vision, e.g. strabismus
• A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes
• G02B 27/01 - Head-up displays
• G06T 19/00 - Manipulating 3D models or images for computer graphics

Abstract

Introduced here are techniques for digitally characterizing the movement of a subject in order to detect the presence of a disorder or monitor the progression of the disorder. More specifically, one or more angular features can be identified that define how certain part(s) of the human body move relative to other part(s) of the human body. These angular feature(s) can be used, for example, to affirmatively diagnose instances of a disorder, eliminate a disorder as the source of symptoms experienced by a subject, generate confidence scores that can be used to assist in diagnosing a subject, monitor disorder progression due to treatment or lack thereof, etc.

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
• G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Abstract

viavia the heating elements.

IPC Classes  ?

• A61N 2/00 - Magnetotherapy
• A61N 2/02 - Magnetotherapy using magnetic fields produced by coils, including single turn loops or electromagnets
• A61N 1/40 - Applying electric fields by inductive or capacitive coupling
• A61N 1/36 - Applying electric currents by contact electrodes alternating or intermittent currents for stimulation, e.g. heart pace-makers
• A61N 1/08 - Arrangements or circuits for monitoring, protecting, controlling or indicating
• A61H 23/02 - Percussion or vibration massage, e.g. using supersonic vibrationSuction-vibration massageMassage with moving diaphragms with electric or magnetic drive
• A61F 7/00 - Heating or cooling appliances for medical or therapeutic treatment of the human body

Abstract

Introduced here are diabetes management platforms able to impute blood glucose level values for a subject whose glycemic health state is being monitored. These imputed values can be used to estimate the glycemic health state of the subject at a given point in time, identify appropriate recommendations for improving the glycemic health state, etc. More specifically, a diabetes management platform can initially acquire one or more explicit data values generated by a glucose monitoring device. The diabetes management platform can then design a statistical model for imputing data values based on the one or more explicit data values. The diabetes management platform may employ several different computational techniques for performing imputation.

IPC Classes  ?

• G16H 20/60 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation

Abstract

A system, method, and apparatus is configured to treat MGD by applying resistive heating and magnetic-based mechanical stimulation of the eyelid. The system includes an underlid device configured to be inserted on the surface of the eye under the eyelid, and a stimulator wand configured to be held by the user on or adjacent to the eyelid in the area of the underlid device. The stimulator wand generates radio frequency (RF) energy that is used to induce an electric current in the underlid device, which is used to excite resistive heating elements that generate heat for heating the meibomian glands. The stimulator wand also generates an oscillating magnetic field that attracts ferromagnetic elements on the underlid device and induces oscillatory movement in the underlid device. The oscillatory movement of the underlid device applies a massaging motion to the meibomian glands while, at the same time, heating the glands via the heating elements.

IPC Classes  ?

• A61N 1/36 - Applying electric currents by contact electrodes alternating or intermittent currents for stimulation, e.g. heart pace-makers
• A61N 1/372 - Arrangements in connection with the implantation of stimulators

Abstract

Systems and methods for peel-off detection for lower power electronics are disclosed. In one embodiment, a device includes: a housing; sensor electronics disposed within the housing; an electrode positioned to receive a charge and output a control signal upon removal of a material positioned proximate to the electrode; an electronic switch configured to control an electrical connection between a power supply and the sensor electronics; and an amplifier electrically coupled to the electrode and configured to receive the control signal from the electrode and output an amplified signal to change a state of the electronic switch based on the control signal.

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• A61B 5/1477 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value using chemical or electrochemical methods, e.g. by polarographic means non-invasive
• G01D 11/24 - Housings

Abstract

Provided herein are compositions and methods for detecting nucleic acids in pooled samples.

IPC Classes  ?

• C12Q 1/70 - Measuring or testing processes involving enzymes, nucleic acids or microorganismsCompositions thereforProcesses of preparing such compositions involving virus or bacteriophage
• C12Q 1/6851 - Quantitative amplification

Abstract

A system, apparatus, and method of operation for focusing a retinal image are described herein. In an embodiment, the retinal imaging system comprises an eyepiece lens assembly; a structured light assembly configured to emit structured illumination light through the eyepiece lens assembly for receipt by an eye positioned adjacent to the eyepiece lens assembly and opposite the structured light assembly; a retinal image sensor optically coupled to the eyepiece lens assembly, wherein the retinal image sensor is positioned to receive the structured illumination light from the eye and is configured obtain a retinal image of a retina of the eye. In an embodiment, the method includes emitting structured illumination light through the eyepiece lens assembly; generating a retinal image based on the structured illumination light received from the retina of the eye; and measuring an edge strength of the structured illumination light from the retinal image.

IPC Classes  ?

• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes
• A61B 3/14 - Arrangements specially adapted for eye photography

Abstract

Techniques for generating structured data for progress tracking using machine learning (ML) are disclosed. In an example method, a computing system receives a document including a number of pages including unstructured data or an event table. The computing system inputs, to an LLM, a prompt and the pages, in which the prompt includes instructions for identifying event tables. The computing system receives, from the LLM, a subset of pages including the event tables. The computing system identifies, for each event table, one or more event columns. The computing system inputs, to the LLM, a second prompt and the event columns, the second prompt including instructions for determining information about one or more clinical trial events from the event columns. The computing system receives, from the LLM, the information and outputs structured schedule information generated by mapping the information to a representation of a clinical trials schedule.

IPC Classes  ?

• G06F 16/242 - Query formulation
• G06F 16/3329 - Natural language query formulation
• G06F 16/35 - ClusteringClassification
• G06F 16/9032 - Query formulation
• G06F 16/906 - ClusteringClassification
• G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires

Abstract

An intraocular implant that includes a micro-display orientated to present image data onto a retina of an eye of a user when the intraocular implant is inside the eye, and a pinhole optic that is arranged to focus the image data presented by the micro-display onto the retina when the implant is inside the eye.

IPC Classes  ?

• A61F 2/16 - Intraocular lenses
• A61F 2/14 - Eye parts, e.g. lenses or corneal implantsArtificial eyes

Abstract

Systems and methods for eye tracking and content tagging in minimally invasive surgical videos are described herein. Minimally invasive surgical videos may be captured while performing robotic surgeries. Robotic surgical systems described herein include robotic arms with interchangeable surgical tools. An endoscope at the end of one of the robotic arms captures video of the surgical procedure. The video is displayed on a display of the surgical system and an eye tracking device captures data corresponding to a gaze direction of the user on the display. Content tags are automatically generated in the image data based on areas of focus of the user. Information within the content tag may be generated based on surgical procedure steps derived from the image data, a log of current surgical procedures, and image data of previous surgical procedures.

IPC Classes  ?

• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• G06N 5/02 - Knowledge representationSymbolic representation
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation

Abstract

To better understand the impact of glycemic events, some entities have begun examining the relationship between the blood glucose level and another physiological parameter. However, this relationship can be difficult to understand. Introduced here are computer programs and associated computer-implemented techniques for discovering glycemic events in a series of data values representative of blood glucose measurements and then altering the measurement schedule of a sensor capable of generating measurements in a dimension other than blood glucose based on the glycemic events. By altering the measurement schedule of the sensor, a diabetes management platform can better understand how, if at all, dimensions other than blood glucose are related to the glycemic health state of a subject whose blood glucose level is being monitored.

IPC Classes  ?

• G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation

Abstract

One example medication container includes a storage portion enclosing a volume to store medication and having an opening providing access to the volume, a cap configured to releasably couple to and seal the storage portion, the cap including one or more visual indicators; a sensor; and an electronic timer, wherein the sensor is configured to output a signal in response to detecting that the cap is decoupled from the storage portion; and the timer is configured to reset based on the signal and to output one or more signals to activate the one or more visual indicators based on an elapsed time since a most recent resetting of the timer and one or more thresholds; and a label affixed to the cap, the label having one or more markers, the one or more markers corresponding to the one or more visual indicators, the markers indicating dosing times associated with a medication.

IPC Classes  ?

• G08B 23/00 - Alarms responsive to unspecified undesired or abnormal conditions
• A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
• A61J 7/04 - Arrangements for time indication or reminder for taking medicine, e.g. programmed dispensers

Abstract

Techniques for predicting immunotherapy outcomes using deep learning are disclosed. In an example method, a computing device receives an image of a tissue sample. The computing device classifies, using a first machine learning model, one or more pathological structures in the tissue sample. The computing device generates, using a second machine learning model, an embedded representation for a first pathological structure from the one or more pathological structures. The computing device determines, using a third machine learning model, a prediction relating to an outcome of applying a therapy. Responsive to the prediction exceeding a predetermined threshold, the computing device outputs an indication corresponding to a likelihood of success of the therapy.

IPC Classes  ?

• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G06T 7/00 - Image analysis
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A model eye for evaluating a retinal imaging system includes a retinal cup, a corneal plate, and a dummy retina. The retinal cup includes an interior concave surface. The corneal plate mates to the retinal cup to define an interior cavity with the interior concave surface of the retinal cup. The dummy retina is formed from a flexible material layer attached to the interior concave surface. The dummy retina mimics a human retina and the flexible material layer includes a plurality of peripheral notches in a perimeter of the flexible material layer to aid the flexible material layer to conform to the interior concave surface.

IPC Classes  ?

• G09B 23/30 - Anatomical models
• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes

Abstract

In one aspect, a gas chromatography-ion mobility spectrometry (GC-IMS) system is disclosed herein. In some embodiments, the GC-IMS system includes a GC column comprising an inlet and an outlet, and a sample delivery system in fluid connection with the inlet of the GC column and configured to provide a sample to the GC column. The GC column is configured to process the sample and produce a processed sample at the outlet. The GC-IMS system may also include an IMS tube. In some embodiments, the IMS tube includes a sample inlet in fluid communication with the outlet of the GC column, a wall that includes an orifice, and an outlet. The sample inlet may be configured to receive a portion of the processed sample. The IMS tube may be configured to analyze a second portion of pressurized gas.

IPC Classes  ?

• G01N 27/622 - Ion mobility spectrometry
• G01N 30/02 - Column chromatography

Abstract

Systems and methods for using a prediction model jointly with a normalization model to provide prediction results are provided. One example method includes receiving an input image of a tissue sample of a patient and generating a normalized image by applying a normalization model on the input image. The normalization model is configured to generate normalized data using input data for a prediction model, and the prediction model is configured to generate prediction results using normalized data generated by the normalization model. The normalization model and the prediction model are jointly trained. The method further includes generating a prediction of disease severity for the patient by applying the prediction model on the normalized image.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06N 3/08 - Learning methods
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Systems and methods for configuring and instructing movement of a surgical device using configuration data from previous surgeries are described herein. Robotic surgical systems described herein include robotic arms with interchangeable surgical tools. The kinematics of the robotic arms are compared against configuration data from previous procedures and differences between the kinematics and the configuration data are identified. The configuration data also includes simulations of robotic surgical systems throughout a procedure. Potential collisions or complications from present and future configurations are identified. The differences and instructions for resolving the differences and potential collisions are presented to a user for correction.

IPC Classes  ?

• G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• A61B 34/32 - Surgical robots operating autonomously
• A61B 90/00 - Instruments, implements or accessories specially adapted for surgery or diagnosis and not covered by any of the groups , e.g. for luxation treatment or for protecting wound edges
• G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A disclosed method includes receiving at least an indication of audio data generated based on sound captured by a microphone of a monitoring device. A set of audio event labels are generated by processing the received audio data with a model that includes audio recognition patterns. Each audio event label is generated by matching an audio pattern in the received audio data with an audio pattern of the audio recognition patterns. The method further includes identifying a hazard event type occurring within a time window of the time period by processing the set of audio event labels with a hazard detection model. In response to detecting the hazard event type, a hazard alert is generated and at least an indication of the hazard alert is communicated to an electronic device other than the monitoring device, which is authorized to receive communications from the monitoring device.

IPC Classes  ?

• G08B 21/04 - Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
• G06N 3/08 - Learning methods
• G06N 20/00 - Machine learning
• G08B 27/00 - Alarm systems in which the alarm condition is signalled from a central station to a plurality of substations
• G10L 15/16 - Speech classification or search using artificial neural networks

Abstract

The present disclosure relates to a machine-learning computing system for training and running a machine-learning model to estimate peptide-retention time for a sample. The machine-learning model can be configured to process inputs that characterize an individual peptide and/or amino acids in the peptide and to output an estimated retention time within a liquid-chromatography column for the peptide. The machine-learning model can include an encoder-decoder model. The encoder and/or the decoder can include a neural network. A subset of peptides can then be identified that are associated with estimated retention times within a specific elution time period during which portion of the sample was eluted from a chromatography column, and mass-spectrometry data can be analyzed to determine which of the subset of peptides are present within the sample.

IPC Classes  ?

• G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• G01N 30/86 - Signal analysis
• G01N 30/88 - Integrated analysis systems specially adapted therefor, not covered by a single one of groups
• G06N 3/08 - Learning methods
• G06N 20/10 - Machine learning using kernel methods, e.g. support vector machines [SVM]
• G16B 35/00 - ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides

Abstract

A system for targeted delivery of a medicament to the gastrointestinal tract (e.g., selectively to the duodenum) of a subject. The system includes a medicament, a mucoadhesive layer at least partially surrounding the medicament, and an enteric coating encasing the medicament and mucoadhesive layer. The enteric coating comprises a material degradable by a pH of the GI tract and a material digestible by a lipase. Also provided are method of making and using the system for targeted delivery of a medicament to the gastrointestinal tract. Also provided are a system for deploying a medicament-containing needle system using an expanding element. The system includes a medicament-containing needle system and an expanding element within a capsule. The capsule is initially coated with an enteric coating. As the enteric coating degrades the expanding element absorbs fluid that enters the capsule and expands to deploy the medicament-containing needle system from the capsule.

IPC Classes  ?

• A61K 9/48 - Preparations in capsules, e.g. of gelatin, of chocolate
• A61K 9/00 - Medicinal preparations characterised by special physical form
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca

Abstract

Introduced here are methods of diagnosing, treating, and preventing inflammatory disorders, such as rheumatoid arthritis. The methods comprise receiving biological information from the subject on a memory component comprising computer-executable programs.

IPC Classes  ?

• C12Q 1/6883 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material

Abstract

Systems, devices, and methods for conducting an eye examination for visual acuity are provided. In one example, a system may include an optical subsystem positioned in front of one or both eyes of a user. The optical subsystem may comprise a handheld device or a head worn device, a visual indicator, and a plurality of vision modifiers. The system may determine a distance between the optical subsystem and the display based on comparing a fixed size of the visual indicator to a detected size of the visual indicator in an image obtained by a camera. The system may output an eye examination image for visual acuity based on the distance being within a valid range. The eye examination image may include a visual stimulus having an output size determined based on the distance. The system may receive an input from the user indicating a selection of the visual stimulus.

IPC Classes  ?

• A61B 3/14 - Arrangements specially adapted for eye photography
• A61B 3/18 - Arrangement of plural eye-testing or -examining apparatus
• G02B 27/01 - Head-up displays

Abstract

The present invention relates to proteomics, and techniques for predicting de novo sequencing of chains of amino acids, such as peptides, proteins, or combinations thereof. Particularly, aspects of the present invention are directed to a computer implemented method that includes obtaining a digital representation of a mass spectrum, the digital representation including a plurality of container elements, encoding, using an encoder portion of a bidirectional recurrent neural network of long short term memory cells and gated recurrent unit cells, each container element as an encoded vector, decoding, using a decoder portion of the bidirectional recurrent neural network, each of the encoded vectors into a sequence of amino acids; and recording the sequence of amino acids as a multi-dimensional data set of amino acids types and a probability of each of the amino acid types in each position of the complete amino acid sequence.

IPC Classes  ?

• G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• G06N 3/044 - Recurrent networks, e.g. Hopfield networks
• G06N 3/084 - Backpropagation, e.g. using gradient descent
• G06N 3/088 - Non-supervised learning, e.g. competitive learning
• G16B 30/00 - ICT specially adapted for sequence analysis involving nucleotides or amino acids
• G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR

Abstract

An intraocular implant and system comprising: an intraocular device coupled to an attachment mechanism operable to transition between a first configuration and a second configuration to secure the intraocular device to the eye; and a delivery device operable to deliver the intraocular device to the eye and manipulate the attachment mechanism to transition between the first configuration and the second configuration.

IPC Classes  ?

• A61F 2/14 - Eye parts, e.g. lenses or corneal implantsArtificial eyes

Abstract

An intraocular implant and system comprising: an intraocular device coupled to an attachment mechanism operable to transition between a first configuration and a second configuration to secure the intraocular device to the eye; and a delivery device operable to deliver the intraocular device to the eye and manipulate the attachment mechanism to transition between the first configuration and the second configuration.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand
• A61B 3/16 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring intraocular pressure, e.g. tonometers
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61F 9/007 - Methods or devices for eye surgery

Abstract

Introduced here are approaches to dynamically verifying the identity of an individual and assessing the health of the individual through objective, algorithmic characterizations of voice features derived from audio recordings created by the individual. These voice features may be paralinguistic features, non-linguistic features, or linguistic features. By characterizing these voice features, insights can be gleaned into how events represented in the audio recordings should be emotionally characterized. For example, for each audio recording created by the individual, a health management platform may calculate a valence measure that is based on the voice features established for that audio recording. These valence measures can be documented, for example, in a profile maintained for the individual, such that changes in health can be detected in a more reliable, quantitative manner.

IPC Classes  ?

• G10L 25/66 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/117 - Identification of persons
• G10L 17/06 - Decision making techniquesPattern matching strategies
• G10L 25/03 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment

Abstract

The technology described herein is related to a two-phase deployment-initiated wakeup mechanism for a body-mountable electronic device. During a first phase of the two-phase wakeup mechanism, a motion sensor detects an acceleration event indicative of deployment of the device onto the body of the user. During a second phase of the two-phase mechanism, control circuitry can be adapted to be enabled by the acceleration event. Once enabled, the control circuitry can verify that the device has been launched onto the body of a user via a deployment applicator in which the device is retained until deployment. Once verified, the control circuitry can wake up the body-mountable electronic device by transitioning the device from a sleep state to a functional (or operational) state.

IPC Classes  ?

• G06F 1/3206 - Monitoring of events, devices or parameters that trigger a change in power modality
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value

Abstract

An ophthalmic camera system includes an eyepiece lens disposed in or on a housing. An image sensor is adapted to acquire a retinal image of the eye through the eyepiece lens. A pupil image sensor acquires an image of a pupil. A controller is coupled to the pupil image sensor for tracking an orientation of the pupil relative to an optical axis of the eyepiece lens. In certain embodiments, the controller fits an ellipse to a periphery of the pupil in the image of the pupil; determines elliptical parameters of the ellipse; and determines a gaze angle of the eye based on the elliptical parameters.

IPC Classes  ?

• A61B 3/14 - Arrangements specially adapted for eye photography
• G06V 40/19 - Sensors therefor
• A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement

Abstract

A computer-implemented method improves efficacy of diabetes self-management to obtain a measurement message and/or contextual activity information used to determine a suitable insulin dosage to treat a patient. The method includes simulating a health coach in a natural conversation to obtain a measurement of the patient's blood-glucose level, processing the measured blood-glucose level with a personalized insulin titration algorithm to determine an insulin dosage recommendation, and generating an electronic signal configured to cause a corresponding action to be performed by a computing device.

IPC Classes  ?

• G16H 20/17 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• G06F 40/30 - Semantic analysis
• G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
• G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
• H04W 88/02 - Terminal devices

Abstract

Introduced here are computer programs and associated computer-implemented techniques for establishing and then maintaining robust wireless communication channels established in accordance with short-range communication protocols. At a high level, two approaches to improving the reliability of these wireless communication channels are described herein. The first approach involves implementing a synchronization scheme in which data is transferred from the container as a series of messages that are arranged in order of increasing payload size and/or decreasing payload priority. The second approach involves employing a wrapper function that is programmed to track the status of wireless connectivity on a more granular level than traditional operating systems.

IPC Classes  ?

• G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
• A61J 7/00 - Devices for administering medicines orally, e.g. spoonsPill counting devicesArrangements for time indication or reminder for taking medicine
• H04W 4/35 - Services specially adapted for particular environments, situations or purposes for the management of goods or merchandise
• H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

Introduced here are approaches to assessing digital images generated during image capture sessions using a machine learning model so as to stratify patients for examination. By applying the machine learning model to the digital images, the patients that are most in need of further examination can be identified to graders. For example, outputs produced by the diagnostic model may trigger the generation and transmission of notifications for patients that are deemed to warrant further examination.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G06T 7/00 - Image analysis

Abstract

Introduced here is an attachable unit that connects to a base unit through a snap-fitting mechanism. The attachable unit can include a top housing structure and a bottom housing structure that are ultrasonically welded together. The top housing structure can include the toe portion that is integral with remaining portions of the top housing structure, where the toe portion is configured to provide the snap-fit with the base unit.

IPC Classes  ?

• H05K 5/00 - Casings, cabinets or drawers for electric apparatus
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• H05K 5/06 - Hermetically-sealed casings
• H05K 5/10 - Casings, cabinets or drawers for electric apparatus comprising several parts forming a closed casing

Abstract

The present disclosure relates to implantable medical devices having protective structures with integrated electrical interconnects. Particularly, aspects of the present disclosure are directed to a medical device that includes a first nest portion and a second nest portion mateable with the first nest portion to form a nest housing. The nest housing includes an interior surface and an exterior surface with a component cavity defined by the interior surface. An electronics module is disposed within a first region of the component cavity. A power source is disposed within a second region of the component cavity. An electrical interconnect is formed on or embedded within the first nest portion, the second nest portion, or a combination thereof. The electrical interconnect electrically connects the electronics module to the power source.

IPC Classes  ?

• H05K 5/00 - Casings, cabinets or drawers for electric apparatus
• H05K 5/02 - Casings, cabinets or drawers for electric apparatus Details
• H05K 5/10 - Casings, cabinets or drawers for electric apparatus comprising several parts forming a closed casing

Abstract

Disclosed is a system for monitoring one or both eyes of a user. The system includes a headset worn by the user and one or more processors. The headset includes a display to generate an output which the user can see while wearing the headset and an eye tracking subsystem to track one or both eyes of the user. The headset can operate alternately in a virtual reality (VR) mode and in a pass through mode. The one or more processors can detect, via the eye tracking subsystem, an eye pattern of one or both eyes of the user. The eye pattern can be detected while the headset is operating in the VR mode. The one or more processors can switch the headset from the VR mode to the pass through mode based on detecting the eye pattern. Other aspects are also described and claimed.

IPC Classes  ?

• G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
• G02B 27/01 - Head-up displays
• A61B 3/02 - Subjective types, i.e. testing apparatus requiring the active assistance of the patient
• G06T 19/00 - Manipulating 3D models or images for computer graphics

Abstract

A diaper pail is disclosed. The diaper pail includes a scale configured to determine a weight of an absorbent article. The diaper pail further includes a light source positioned to transmit light at an excitation wavelength of a biological substance. The diaper pail further includes a photodetector positioned to detect a measurement of light intensity within the range of emission wavelengths of the biological substance. The diaper pail includes a processor that is configured to execute processor-executable instructions to receive the weight of the absorbent article and the measurement of light intensity and to detect a presence of the biological substance on the absorbent article.

IPC Classes  ?

• B65F 1/16 - Lids or covers
• B65F 1/14 - Other constructional features
• G01G 19/52 - Weighing apparatus combined with other objects, e.g. with furniture
• G01G 19/62 - Over or under weighing apparatus
• G01N 21/64 - FluorescencePhosphorescence
• G08B 13/14 - Mechanical actuation by lifting or attempted removal of hand-portable articles

Abstract

Introduced here are health management platforms able to monitor changes in the health state of a subject based on the context of digital activities performed by, or involving, the subject. Initially, a health management platform can identify a physiological response by examining physiological data associated with a subject. Then, the health management platform can identify a stimulus presented by an electronic device that provoked the physiological response by examining contextual data associated with the subject. The contextual data may be in the form of a screenshot of a computer program in use by the subject during the physiological response. In some embodiments, the health management platform prompts the subject to specify whether the physiological response is a positive physiological response that resulted in an upward shift in health or a negative physiological response that resulted in a downward shift in health.

IPC Classes  ?

• G06V 20/40 - ScenesScene-specific elements in video content
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
• G06T 7/20 - Analysis of motion
• G06V 40/20 - Movements or behaviour, e.g. gesture recognition
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• H04W 4/21 - Services signallingAuxiliary data signalling, i.e. transmitting data via a non-traffic channel for social networking applications
• H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

An ophthalmic device can be configured for active drug delivery. The ophthalmic device can include a body; a reservoir positioned within the body and configured to store at least one drug; and a metal cap configured to cover an opening of the reservoir. The metal cap can be dissolved by application of an electrical signal, which can actively release the at least one drug from the reservoir upon receipt of an electrical signal and create reaction products. At least one of the electrical signal and the reaction products may cause degradation of the at least one drug. Water from the eye can also cause problems with degradation. Accordingly, a shielding material can be utilized as a barrier or defender to protect the drug from degradation due to the active release.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand
• A61N 1/04 - Electrodes

Abstract

An eye dropper with sensors that allows for delivery of a specific or controlled dose of a therapeutic agent in vapor form to a patient's eye is provided.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand

Abstract

An intraocular pressure measurement system comprising: an intraocular implant having a pressure sensor implantable in an eye, wherein the pressure sensor defines an optical cavity with a depth that varies based on an intraocular pressure of the eye; and an external reader device having a number of laser light sources configured to emit a plurality of beams and project an array of spots formed from the plurality of beams onto the pressure sensor, and a detector configured to receive a reflection of the array of spots off the pressure sensor that is used to measure the intraocular pressure of the eye.

IPC Classes  ?

• A61B 3/16 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring intraocular pressure, e.g. tonometers
• A61B 3/15 - Arrangements specially adapted for eye photography with means for aligning, spacing or blocking spurious reflection

Abstract

In an exemplary aspect, a method of generating an anonymized video from a source video is disclosed. The method includes generating an image data set comprising a set of landmarks, a set of classifications, and a synthesized feature vector based on a frame of the source video. Generating the image data set may include determining a feature vector based on the frame, and generating the synthesized feature vector as a weighted average of a plurality of feature vectors selected from a subset of feature vectors of a data set, wherein the subset of feature vectors are determined as the closest neighbors to the feature vector from among the data set. The method may further include encoding the image data set to produce an encoded vector; generating a synthesized frame based on the encoded vector; and generating the anonymized video based on the synthesized frame and the source video.

IPC Classes  ?

• G06T 5/60 - Image enhancement or restoration using machine learning, e.g. neural networks
• G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
• G06T 3/00 - Geometric image transformations in the plane of the image
• G06N 3/02 - Neural networks
• G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
• G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Introduced here is a module for converting single-cell data sets to transformed bulk-cell datasets for use in augmenting single-cell data, identifying cell type subsets, and in assessing factors associated with diseases. Such cell type subsets include immune cell subsets.

IPC Classes  ?

• C12Q 1/6869 - Methods for sequencing
• C12Q 1/6881 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for tissue or cell typing, e.g. human leukocyte antigen [HLA] probes
• G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
• G16B 25/00 - ICT specially adapted for hybridisationICT specially adapted for gene or protein expression
• G16B 40/30 - Unsupervised data analysis

Abstract

One disclosed example method for simulated medical images using GANs includes receiving, by a generative adversarial network (“GAN”), a plurality of training images, the training images associated with an affliction and depicting different stages of progression for the affliction; generating, using the GAN, a latent space based on the training images, the latent space comprising a first set of data points indicating parameters associated with the training images; generating, using the GAN, a second set of data points in the latent space based on simulated images generated from the latent space, the simulated images based at least in part on the first set of data points; after generating the second set of data points: receiving a request for a first simulated image associated with the affliction; and generating and outputting, by the GAN, the first simulated image based on the latent space.

IPC Classes  ?

• G06F 18/214 - Generating training patternsBootstrap methods, e.g. bagging or boosting
• G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
• G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• G06N 3/045 - Combinations of networks

Abstract

Systems, devices, and methods for determining a standoff distance to an eye are provided. In one example, a system may include a structure along a first axis toward an eye, a linear sensor array, and a light source to emit a beam of light toward the linear sensor array along a second axis. The beam of light may comprise a width such that a first portion of the beam of light illuminates a lateral surface of the eye and a second portion of the beam of light passes in front of the eye. The system may determine, based on a measurement of the second portion, a standoff distance between the structure and the eye along the first axis. Another example may include an ultrasonic transducer assembly to emit an ultrasonic pulse toward the eye and detect a reflection of the pulse to determine the standoff distance.

IPC Classes  ?

• A61B 3/14 - Arrangements specially adapted for eye photography
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes
• A61B 3/13 - Ophthalmic microscopes
• A61B 3/16 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring intraocular pressure, e.g. tonometers

Abstract

Systems, devices, and methods for determining a standoff distance to an eye are provided. In one example, a system may include a structure along a first axis toward an eye, a linear sensor array, and a light source to emit a beam of light toward the linear sensor array along a second axis. The beam of light may comprise a width such that a first portion of the beam of light illuminates a lateral surface of the eye and a second portion of the beam of light passes in front of the eye. The system may determine, based on a measurement of the second portion, a standoff distance between the structure and the eye along the first axis. Another example may include an ultrasonic transducer assembly to emit an ultrasonic pulse toward the eye and detect a reflection of the pulse to determine the standoff distance.

IPC Classes  ?

• A61B 3/16 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring intraocular pressure, e.g. tonometers
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes

Abstract

An active drug dispensing ophthalmic device can include a plurality of drug reservoirs, each covered by an electrode, and a controller-responder architecture. Electrodissolution of each electrode and the associated drug release can be governed by a controller via a responder. Employing a controller-responder architecture can reduce the number of connections and separate electrical signals required to actively dispense drugs from each of the plurality of drug reservoirs. The controller can be connected to a plurality of responders via a control line bundle and each of the plurality of responders can deliver signals to the electrode(s) covering a portion of a plurality of drug reservoirs. The controller-responder architecture can also employ a composite electrical communication signal to even further decrease the number of electrical connections required from a controller to each of the responders.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand
• A61K 9/00 - Medicinal preparations characterised by special physical form

Abstract

Systems and methods for filter-based multispectral fluorescence microscope optimized for virtual staining techniques are provided. An example imaging system includes an excitation module, an emission module, and a sample stage configured to support a sample. The excitation module is configured to transmit light to the sample to cause fluorescence that is detectable by the emission module. The excitation module includes dichroic mirrors and light sources arranged in a tree configuration based on the positions of the dichroic mirrors. The emission module is configured to capture the emitted fluorescence from the sample. The emission module includes dichroic mirrors and image sensors, in which each image sensor is configured to receive fluorescence of a particular color emitted from the sample responsive to excitation light of a particular color and are arranged in a tree configuration based on the positions of the dichroic mirrors.

IPC Classes  ?

• G01N 21/64 - FluorescencePhosphorescence
• G02B 21/06 - Means for illuminating specimen
• G01J 3/44 - Raman spectrometryScattering spectrometry

Abstract

Systems, devices, and methods for detecting a visual indicator of an occluder for an eye examination are provided. In one example, a device may be used to administer an eye examination by detecting, via a camera of the device, a visual indicator located on an occluder while the occluder is covering at least a portion of a user's face. The device can configure a graphical user interface to display, at a display screen of the device, an eye examination administered to the user. The device can output, via the display screen, a result of the eye examination based on information encoded by the visual indicator. In some implementations, the detecting may include detecting an opaque surface of the occluder covering an eye of the user. In some implementations, the detecting may include detecting a lens of the occluder covering an eye of the user.

IPC Classes  ?

• A61B 3/028 - Subjective types, i.e. testing apparatus requiring the active assistance of the patient for testing visual acuitySubjective types, i.e. testing apparatus requiring the active assistance of the patient for determination of refraction, e.g. phoropters
• A61B 3/00 - Apparatus for testing the eyesInstruments for examining the eyes

Abstract

Systems and methods implementing release and capture techniques for insect population monitoring and control are disclosed. In an example method for releasing shipped insects, shipping containers for transporting insects are received. For each shipping container, a holding containers is prepared by transferring the insects to the holding container. Sustenance is provided for the insects. The insects are released from each holding container after predetermined amount of time.

IPC Classes  ?

• A01K 1/08 - Arrangements for simultaneously releasing several animals
• A01M 1/10 - Traps
• B65D 81/18 - Containers, packaging elements, or packages, for contents presenting particular transport or storage problems, or adapted to be used for non-packaging purposes after removal of contents providing specific environment for contents, e.g. temperature above or below ambient
• B65D 83/00 - Containers or packages with special means for dispensing contents
• B65D 85/50 - Containers, packaging elements or packages, specially adapted for particular articles or materials for living organisms, articles or materials sensitive to changes of environment or atmospheric conditions, e.g. land animals, birds, fish, water plants, non-aquatic plants, flower bulbs, cut flowers or foliage
• A01K 1/03 - Housing for domestic or laboratory animals
• A01N 63/20 - BacteriaSubstances produced thereby or obtained therefrom
• A01P 23/00 - Chemosterilants
• A01K 67/033 - Rearing or breeding invertebrates; New breeds of invertebrates

Abstract

An intraocular implant comprising: a pressure sensor implantable in an eye, wherein the pressure sensor comprises a substrate having a first side coupled to a membrane to define an optical cavity with a depth that varies based on an intraocular pressure of the eye; and an enclosure coupled to a second side of the substrate to define a hermetic cavity comprising a light source and a detector operable to interrogate the pressure sensor and obtain data corresponding to an intraocular pressure of the eye based on the interrogation.

IPC Classes  ?

• A61B 3/16 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring intraocular pressure, e.g. tonometers
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand

Abstract

In one aspect, a gas chromatography-ion mobility spectrometry (GC-IMS) system is disclosed herein. In some embodiments, the GC-IMS system includes a GC column comprising an inlet and an outlet, and a sample delivery system in fluid connection with the inlet of the GC column and configured to provide a sample to the GC column. The GC column is configured to process the sample and produce a processed sample at the outlet. The GC-IMS system may also include an IMS tube. In some embodiments, the IMS tube includes a sample inlet in fluid communication with the outlet of the GC column, a wall that includes an orifice, and an outlet. The sample inlet may be configured to receive a portion of the processed sample. The IMS tube may be configured to analyze a second portion of pressurized gas.

IPC Classes  ?

• G01N 27/622 - Ion mobility spectrometry
• G01N 30/02 - Column chromatography

Abstract

An intraocular implant comprising: a pressure sensor implantable in an eye, wherein the pressure sensor comprises a substrate having a first side coupled to a membrane to define an optical cavity with a depth that varies based on an intraocular pressure of the eye; and an enclosure coupled to a second side of the substrate to define a hermetic cavity comprising a light source and a detector operable to interrogate the pressure sensor and obtain data corresponding to an intraocular pressure of the eye based on the interrogation.

IPC Classes  ?

• A61B 3/16 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring intraocular pressure, e.g. tonometers
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

An active drug dispensing ophthalmic device can include a plurality of drug reservoirs, each covered by an electrode, and a controller-responder architecture. Electrodissolution of each electrode and the associated drug release can be governed by a controller via a responder. Employing a controller-responder architecture can reduce the number of connections and separate electrical signals required to actively dispense drugs from each of the plurality of drug reservoirs. The controller can be connected to a plurality of responders via a control line bundle and each of the plurality of responders can deliver signals to the electrode(s) covering a portion of a plurality of drug reservoirs. The controller-responder architecture can also employ a composite electrical communication signal to even further decrease the number of electrical connections required from a controller to each of the responders.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand
• A61M 31/00 - Devices for introducing or retaining media, e.g. remedies, in cavities of the body

Abstract

A therapeutic agent delivery device is provided. The device can include: a vapor chamber configured to be positioned about an eye of a patient to deliver a therapeutic agent in vapor form to a tear film of a patient's eye; a therapeutic agent source comprising a therapeutic agent in communication with the vapor chamber; a heater or vacuum in communication with the vapor chamber and the therapeutic agent source, the heater or vacuum configured to convert the therapeutic agent in the therapeutic agent source into a vapor form; and a controller compartment operably coupled to the vapor chamber and comprising a timer and a microcontroller.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyesDevices for putting in contact-lensesDevices to correct squintingApparatus to guide the blindProtective devices for the eyes, carried on the body or in the hand
• A61F 9/007 - Methods or devices for eye surgery