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A Method, Device, and Apparatus for Predictive Analytics and Movement Tracking

IP.com Disclosure Number: IPCOM000240527D
Publication Date: 2015-Feb-05
Document File: 3 page(s) / 49K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a wearable movement detection device and associated system that remind the user to move during a busy schedule (i.e. that includes a lot of sedentary time) and integrates with the daily calendar to find and prompt movement during optimal times of the day. The device and system combine tracking and predictive analytics capabilities.

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Page 01 of 3

A Method, Device, and Apparatus for Predictive Analytics and Movement Tracking

When a person is diagnosed with pulmonary embolisms (a blockage of an artery in the lungs due to blood clots), the person can undergo a challenging recovery, which includes avoiding sitting still for long periods to keep circulation going. This is a challenge for the busy person whose calendar often has long stretches of back-to-back meetings and air travel.

The novel solution to this problem is a wearable device that not only tracks and analyzes movement, but also is predictive. The novel device is a wearable movement capture device that integrates with the busy lifestyles of working professionals. The device reminds the user to move during a busy schedule and integrates with the daily calendar to find and prompt movement during optimal times when blocks of calendar events are scheduled.

As a "truly wearable" device, it can be mounted into clothing, wristbands, and other accessories. The device tracks movement and transmits to a Cloud server. An associated application performs predictive analysis and visualizes the user's movement data. The system integrates with the user's web-based calendar to detect blocks of time in which the user may not be moving; it then promotes movement. This is predictive, unlike current wearables that detect when the user has not moved for a certain period.

The novel movement device and associated system are comprised of the following:


 Device: equipped with a wireless Internet connectivity system


 Five Micro-Electromechanical Sensors (MEMS): accelerometer, gyroscope, eCompass, pressure, humidity, and temperature


 Bluetooth* Low Energy for connectivity to a smart device


 Smartphone/tablet application: receives data from the device and transmits data to the cloud


 Cloud server: to collect movement data and transmit events to/from the device and integrated applications


 Cloud platform: used to gather transmitted data from the cloud, analyze movement data, integrate with calendaring, and provide user interfaces

Using current movement information and calendar information as well as given parameters, the novel device and associated system predicts when the user ought to be moving. It then automatically blocks time on the user's calendar or encourages the user to move earlier than scheduled (if moving at the scheduled time is likely to cause a business conflict). As the day progresses, and when the wearer moves or if the wearer moves during different times of the day, the device resets the designated movement time(s).

Figure: Components and process for preferred embodiment

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Page 02 of 3

Example Embodiments


Assume the following parameters:


 Maximum time between movement is 120 Minutes


 Minimum time between movements is 15 minutes


 Margin of flexibility is five (5) minutes


 Start analysis time is at 06:00 and stop time is 22:00

Use...