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Real time forecasting of potential health incident based on time to help, and initiation of advanced precautionary communication to user and relevant people Disclosure Number: IPCOM000253941D
Publication Date: 2018-May-16
Document File: 3 page(s) / 388K

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The Prior Art Database

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Real Time Forecasting of Potential Health Incident Based on Time to Help, and Initiation of Advanced Precautionary Communication to User and Relevant People Disclosed is a system for forecasting the health status of the user of a device, the time to help this user in case of an emergency and the possibility of a health incident, and for alerting both the user and relevant nearby people. Currently the art exists which allows the monitoring of health indicators real time location and current speed. However, there is no art which forecasts a potential medical incident by comparing current vitals, real time location and speed against historical data, which forecasts time to help from emergency services and nearby people based on location and traffic conditions, and which alerts all relevant parties to the potential of a medical emergency. Problem With technology playing a huge part of our daily lives, monitoring and recording a person’s vitals and environment has never been easier from a day to day stand point. This information can be stored and analysed by a doctor at some future date. However, there is no current solution which uses all this data that is gathered to forecast if the person could potentially be at risk, based on what activities they are performing and based on how long it would take for help to come if some life-threatening event was to happen. Therefore, while vitals and environment data are being captured real time, predictive analysis using this data is not available. Because appropriate alerts is not given to a person, it is possible that when life-threatening event happens that person will be too far from help. Solution The forecast of the health status of the user of a device is based on historical health data, real time health data, historical patterns of activity, speed, acceleration, direction and incline & decline in the route. As shown in figure 1, the solution leverages monitoring of vitals, real time location and current speed and direction being automatically pushed to the Cloud. There the solution uses this information to compare to previous data points and baseline data points, to determine the current health status of the person and to forecast a health anomaly if the current actions the person is doing were to continue...