Falls are a major problem for older adults. A continuous, unobtrusive, environmentally mounted in-home monitoring system that automatically detects when falls have occurred or when the risk of falling is increasing could alert health care providers and family members so they could intervene to improve physical function or mange illnesses that are precipitating falls. Researchers at the University of Missouri (MU)Center for Eldercare and Rehabilitation Technology are testing such sensor systems for fall risk assessment and detection in older adults' apartments in a senior living community. Initial results comparing ground truth fall risk assessment data and GAITRite gait parameters with gait parameters captured from Mircosoft Kinect and Pulse-Dopplar radar are reported. Falls are a major problem in older adults. One in every three people over the age of 65 falls each year and 2 million are treated in emergency rooms for fall-related injuries (Centers for Disease Control, 2013). Researchers have studied falls, fall risk assessment, and interventions to prevent falls. However, their methods require that research staff or clinicians complete multi-factorial assessment of fall risk (Parrell et al, 2001) or that people maintain logs of falls, wear devices that measure changes in positions that could indicate a NIH Public Access
Rantz developed a continuous, unobtrusive, and environmentally mounted in-home fall risk assessment and detection system using the Kinect REF .
In-Home Fall Risk Assessment and Detection Sensor System
Journal of Gerontological Nursing
Journal of Gerontological Nursing
Medicine