Falls among the older population are one of the most common causes for injuries, frailty and for morbidity. Fall incidents have various reasons and are often related to decreased mobility and hence an increasing fall risk could be detected in time. The objective of this paper is to show results and future prospects of the funded project vitaliSHOE and in detail of an automated multi-sensor-based method to determine fall risk indicators in older people’s gait and body movements.
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