Background: About a third of home-dwelling older people fall each year, and institutionalized older people even report a two- or threefold higher rate for falling. Automatic fall detection systems have been developed to support the independent and secure living of the elderly. Even though good fall detection sensitivity and specificity in laboratory settings have been reported, knowledge about the sensitivity and specificity of these systems in real-life conditions is still lacking.
Objective: The aim of this study was to evaluate the long-term fall detection sensitivity and false alarm rate of a fall detection prototype in real-life use.
Methods: A total of 15,500 h of real-life data from 16 older people, including both fallers and nonfallers, were monitored using an accelerometry-based sensor system with an implemented fall detection algorithm.
Results: The fall detection system detected 12 out of 15 real-life falls, having a sensitivity of 80.0%, with a false alarm rate of 0.049 alarms per usage hour with the implemented real-time system. With minor modification of data analysis the false alarm rate was reduced to 0.025 false alarms per hour, equating to 1 false fall alarm per 40 usage hours.
Conclusion: These data suggest that automatic accelerometric fall detection systems might offer a tool for improving safety among older people.
© 2014 S. Karger AG, Basel.