Frail persons are considered to be particularly vulnerable to falls. Diagnostic tools typically consider the Fried factors such as weight loss, self-reported fatigue, weakness, slow walking speed and low physical activity. Screening these factors is time consuming and difficult to apply in primary care. In case of a fall event, the impact can vary. The longer people are laying on the ground, the more serious the consequences are. There are already various emergency systems, but above all, the sensitivity of the automatic fall detection is still low. Furthermore, there is little data on possible connections between movement indicators and frailty so far.
Thus, the EU-funded FRAIL project focuses on the optimization of an existing fall detection algorithm and the comparison of frailty scoring with smartwatch motion indicators.