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Method and System for Improving Continuous Glucose Monitor Predictive Analytics by Incorporating Personal Information

IP.com Disclosure Number: IPCOM000236626D
Publication Date: 2014-May-06
Document File: 1 page(s) / 21K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for improving Continuous Glucose Monitor (CGM) predictive analytics by incorporating personal information for people with diabetes.

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Method and System for Improving Continuous Glucose Monitor Predictive Analytics by Incorporating Personal Information

Continuous Glucose Monitor (CGM) remotely reads blood glucose levels for people with diabetes and sends blood glucose levels to a monitor. The monitor displays the current blood glucose levels based on the rate of change. In addition, the CGM also predicts high and low values of blood glucose levels. The prediction of high and low values does not depend on individualized trends for a person with diabetes.

Disclosed is a method and system for improving Continuous Glucose Monitor (CGM) predictive analytics by incorporating personal information for people with diabetes. The method and system applies a modification to computer program incorporated into the CGM. The modification provides a second level of predictive analytics by incorporating personal information of an individual to improve predictions of high and low blood glucose levels. The personal information can be, but is not limited to, a personal history of the individual.

The method and system introduces an additional model to predict the future blood glucose levels. The additional model finds historical similarities for the individual based on factors such as, but not limited to, insulin on board taking into account last usage and dosage of insulin, changes in heart rate that is significant for identifying increased exercise, time of day to estimate glucose sensitivity of the individual and...