# US 2022/0037017 A1 · Remote medicine based on video link and sensor data

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- Number: US 2022/0037017 A1
- Document ID: US20220037017A1
- Status: Published application
- Kind: A1
- Application number: 17/391,928
- Filed: 2021-08-02
- Published: 2022-02-03
- Earliest claimed: 2020-08-03
- Assignees: Healthcare Integrated Technologies, Inc.
- Applicants: Healthcare Integrated Technologies Inc.
- Inventors: Kenneth M. GREENWOOD; Scott Michael BORUFF; Jurgen VOLLRATH
- Web page: https://patentgrep.com/patent/US20220037017A1

## CPC

- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- G16H 40/67: for remote operation
- A61B 5/1117: {Fall detection}
- A61B 5/1128: {using image analysis (A61B5/1127 takes precedence)}
- A61B 5/7246: {using correlation, e.g. template matching or determination of similarity}
- A61B 5/7267: {involving training the classification device}
- A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)}
- A61B 5/746: {Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms}
- G08B 21/043: {detecting an emergency event, e.g. a fall}
- G16H 10/60: for patient-specific data, e.g. for electronic patient records
- G16H 40/63: for local operation
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G16H 50/30: for calculating health indices; for individual health risk assessment
- G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients
- G16H 80/00: ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
- A61B 5/022: by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers
- A61B 5/02438: {with portable devices, e.g. worn by the patient}
- A61B 5/14542: {for measuring blood gases (A61B5/14551 takes precedence)}
- G08B 21/0476: {Cameras to detect unsafe condition, e.g. video cameras}
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G08B: SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS

## Abstract

A method and system for performing telemedicine includes a real time video conference session between patient and physician coupled with patient physiology sensors for facilitating an initial diagnosis, followed by an ad hoc set of medical sensors to assist in defining a refined diagnosis.

## Claims

### Claim 1

A method for performing remote medicine (telemedicine), comprising:
receiving a request for a remote medical session,
connecting the patient to a medical practitioner through a video link,
establishing an initial remote diagnosis based on one or more of:
a) a discussion, via the video link, between the medical practitioner and one or more of: the patient, and an authorized support person (also referred to as a care-provider), and
b) data from one or more physiological sensors that provide ongoing monitoring of the patient, and
validating the initial remote diagnosis by capturing medical data using one or more medical sensors that the patient, a care-provider, or other person is instructed to apply or use with the patient as part of the remote medical session.

### Claim 2 (depends on 1)

The method of claim 1, wherein, following the validation of the initial remote diagnosis, at least one of the following follow-up procedures are invoked: the patient is required to attend an in-person visit with a medical practitioner, and one or more medical sensors are delivered to the patient for future remote medical sessions.

### Claim 3 (depends on 1)

The method of claim 1, wherein the medical practitioner is provided with copies of the discussion, data from any physiological sensors, and data from the medical sensors for inclusion in an electronic medical record of the patient.

### Claim 4 (depends on 1)

The method of claim 1, wherein ongoing monitoring by physiological sensors includes continuous monitoring, or capturing data at regular intervals, or in response to identified events.

### Claim 5 (depends on 4)

The method of claim 4, wherein the identified events include events triggered by the patient, and anomalies detected by a physiological sensor.

### Claim 6 (depends on 5)

The method of claim 5, wherein an artificial intelligence system is used for identifying anomalies in physiological sensor data.

### Claim 7 (depends on 6)

The method of claim 6, wherein data from the physiological sensors and data from the medical sensors is processed by the artificial intelligence system to identify correlations between at least one of: physiological sensor data and medical sensor data for a related time frame, and medical sensor data with previously identified events, in order to improve the diagnosis of a condition and to provide refined training data for the artificial intelligence system.

### Claim 8 (depends on 7)

The method of claim 7, wherein the process of identifying correlations includes identifying anomalies in the data of one or more sensors during an identified event or at a time interval preceding or following an identified event.

### Claim 9 (depends on 6)

The method of claim 6, wherein the request for a remote medical session is initiated by a medical practitioner, by the patient, by a third party, by the artificial intelligence system in response to an anomaly, or at defined intervals as part of a preventative health check-up.

### Claim 10

A system for providing telemedicine, comprising:
a physician communication platform,
a patient communication platform, wherein the communication platforms are adapted to conduct a video communication session between the patient and physician communication platforms,
one or more physiological sensors (also referred to as patient monitoring devices) that perform ongoing monitoring of the patient,
one or more medical sensors, and
a server system for collecting data from the communication session between physician and patient, data from the one or more physiological sensors, and data from the one or more medical sensors, wherein the server system includes a processor connected to memory which includes machine-readable code defining an algorithm for analyzing the data from at least one of: the data from a physiological sensor, and data from a medical sensor, to identify a physiological conditions (also referred to herein as a flagging event).

### Claim 11 (depends on 10)

The system of claim 10, wherein the algorithm forms part of an artificial intelligence (AI) network, which is configured to identify anomalies and events in the data of the physiological sensors over time.

### Claim 12 (depends on 11)

The system of claim 11, wherein anomalies detected by the AI network are correlated with data for the same time frame or a related prior or subsequent timeframe from the same or other physiological sensors.

### Claim 13 (depends on 11)

The system of claim 11, wherein the AI network includes data inputs from the medical sensors to identify anomalies in the medical sensor data during a session, and correlations with anomalies in the physiological sensors, thereby defining a flagging event.

### Claim 14 (depends on 13)

The system of claim 13, wherein a flagging event includes a pre-defined event such as a falling event, or an anomaly in the data from a physiological sensor that exceeds a predefined threshold, or an anomaly in the data from a physiological sensor that correlates with an anomaly in the data from at least one other physiological sensor for the same or a related time-frame.

### Claim 15 (depends on 12)

The system of claim 12, wherein the algorithm includes logic to trigger a communication session if a flagging event is identified.

### Claim 16 (depends on 10)

The system of claim 10, wherein the physician communication platform includes a screen, a processor, and access to the internet, and a portal accessible through a browser or an app that allows the physician to conduct a video call with the patient and access data from any of the physiological sensors and medical sensors, and download the data from the video call and sensors.