Citation

Krenzel D, Warren S, Li K, Natarajan B, Singh G. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2012; 2012: 4042-4045.

Copyright

(Copyright © 2012, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/EMBC.2012.6346854

PMID

23366815

Abstract

Accidental slips and falls due to decreased strength and stability are a concern for the elderly. A method to detect and ideally predict these falls can reduce their occurrence and allow these individuals to regain a degree of independence. This paper presents the design and assessment of a wireless, wearable device that continuously samples accelerometer and gyroscope data with a goal to detect and predict falls. Lyapunov-based analyses of these time series data indicate that wearer instability can be detected and predicted in real time, implying the ability to predict impending incidents.

Language: en