Remote Automatic Fall Detection and Activity Monitoring using Smart Wearables
Loading...
Author
Moufawad El Achkar, Christopher
Jorge, João
Muntané Calvo, Enric
Gerber, Mickael
Lemkaddem, Alia
Lemay, Mathieu
Verjus, Christophe
DOI
Abstract
A timely alarm after a fall can save the faller's life and reduce the risk of debilitating injuries. In a connected world, wearable sensors offer a massive opportunity to accurately detect falls and send immediate alarms to family and healthcare providers. At CSEM, we have developed real-time embedded algorithms for unobtrusive fall detection focused on context and activity classification. These algorithms can detect falls more accurately while rejecting false positives. Our solutions target sensors embedded in non-stigmatizing widely available wearable devices.
Publication Reference
CSEM Scientific and Technical Report 2020, p. 96
Year
2020