Automated Fall Risk Assessment and Detection in the Home: A Preliminary Investigation

Falls are a major problem for older adults. A continuous unobtrusive in-home monitoring system that provides an accurate automated assessment of fall risk and detects when falls have occurred would allow for timely intervention and prevention allowing individual to remain healthier and independent longer. Sensor networks have been installed in apartments of older adult volunteers at TigerPlace, an independent senior living community. Initial results comparing gait parameters captured with a Microsoft Kinect with ground truth clinical fall risk assessments and GAITRite data are presented.

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