Wireless slips and falls prediction system.
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.
Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS, USA.
Devon
D
Krenzel
Steve
S
Warren
Kejia
K
Li
Bala
B
Natarajan
Gurdip
G
Singh
D061725:Accelerometry; D000058:Accidental Falls; D000465:Algorithms; D006801:Humans; D013686:Telemetry / Q000379:methods*; D016138:Walking; D059015:Wireless Technology