@inproceedings{aa522c01ef8f49c4a73fb2be635161e8,
title = "Wireless slips and falls prediction system",
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.",
keywords = "Accelerometer, Android smart phone, Lyapunov exponents, ZigBee wireless, gyroscope, wearable devices",
author = "Devon Krenzel and Steve Warren and Kejia Li and Bala Natarajan and Gurdip Singh",
year = "2012",
doi = "10.1109/EMBC.2012.6346854",
language = "English (US)",
isbn = "9781424441198",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
pages = "4042--4045",
booktitle = "2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012",
note = "34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 ; Conference date: 28-08-2012 Through 01-09-2012",
}