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Method and System for Annotating Encounter Readings with Potential Variance in Heat Rate Readings of a User

IP.com Disclosure Number: IPCOM000248674D
Publication Date: 2016-Dec-24
Document File: 1 page(s) / 64K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for annotating encounter readings with potential variance in heart rate reading of a user. The method and system calculates potential variance in heart rate readings of the user by comparing abnormal readings of the user with prior heart rate readings associated with similar activity, location, time and population.

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Method and System for Annotating Encounter Readings with Potential Variance in Heat Rate Readings of a User

Disclosed is a method and system for annotating encounter reading with potential variance in heart rate readings of a user. The method and system calculates potential variance in heart rate readings of the user by comparing abnormal readings of the user with prior heart rate readings associated with similar activity, location, time and population.

The method and system is integrated with the user’s wearable computing device which may include, but need not be limited to, a smart watch, smart glasses and the like for collecting data from the user’s body. The wearable computing device gathers vital signs of the user including, but need not be limited to, heart rate and blood pressure along with user’s activities and location/event information.

Moving on, the system builds a data model based on the data gathered from the user’s wearable computing device. The data thus collected is categorized into appropriate categories such as Vital Sign, User Action, Time and Location.

In an instance, the method and system also collects user’s sentiment data and stores the user’s data into a database such as an Electronic Medical Record System (EMR) and the like.

The system uses the data model for analyzing the encountered readings of a user on detecting an abnormal reading of the user. The system compares the abnormal reading of the user with prior readings with similar activities / events / locations and analyzes a cause of the abnormal reading on identifying that the user’s abnormal reading is matching with the prior read...