Determination of simple thresholds for accelerometry-based parameters for fall detection

The increasing population of elderly people is mainly living in a home-dwelling environment and needs applications to support their independency and safety. Falls are one of the major health risks that affect the quality of life among older adults. Body attached accelerometers have been used to detect falls. The placement of the accelerometric sensor as well as the fall detection algorithms are still under investigation. The aim of the present pilot study was to determine acceleration thresholds for fall detection, using triaxial accelerometric measurements at the waist, wrist, and head. Intentional falls (forward, backward, and lateral) and activities of daily living (ADL) were performed by two voluntary subjects. The results showed that measurements from the waist and head have potential to distinguish between falls and ADL. Especially, when the simple threshold-based detection was combined with posture detection after the fall, the sensitivity and specificity of fall detection were up to 100 %. On the contrary, the wrist did not appear to be an optimal site for fall detection.