Citation

Deutsch M, Burgsteiner H. Stud. Health Technol. Inform. 2016; 223: 259-266.

Affiliation

Institute for eHealth, Graz University of Applied Sciences, Graz, Austria.

Copyright

(Copyright © 2016, IOS Press)

DOI

unavailable

PMID

27139412

Abstract

The growing number of elderly people in our society makes it increasingly important to help them live an independent and self-determined life up until a high age. A smartwatch-based assistance system should be implemented that is capable of automatically detecting emergencies and helping elderly people to adhere to their medical therapy. Using the acceleration data of a widely available smartwatch, we implemented fall detection and inactivity recognition based on a smartphone connected via Bluetooth. The resulting system is capable of performing fall detection, inactivity recognition, issuing medication reminders and alerting relatives upon manual activation. Though some challenges, like the dependence on a smartphone remain, the resulting system is a promising approach to help elderly people as well as their relatives to live independently and with a feeling of safety.

Language: en