@article{ref1,
title="Mobile phone-based pervasive fall detection",
journal="Personal and ubiquitous computing",
year="2010",
author="Dai, Jiangpeng and Bai, Xiaole and Yang, Zhimin and Shen, Zhaohui and Xuan, Dong",
volume="14",
number="7",
pages="633-643",
abstract="Falls are a major health risk that diminishes the quality of life among the elderly people. The importance of fall detection increases as the elderly population surges, especially with aging &quot;baby boomers&quot;. However, existing commercial products and academic solutions all fall short of pervasive fall detection. In this paper, we propose utilizing mobile phones as a platform for developing pervasive fall detection system. To our knowledge, we are the first to do so. We propose PerFallD, a pervasive fall detection system tailored for mobile phones. We design two different detection algorithms based on the mobile phone platforms for scenarios with and without simple accessories. We implement a prototype system on the Android G1 phone and conduct extensive experiments to evaluate our system. In particular, we compare PerFallD's performance with that of existing work and a commercial product. The experimental results show that PerFallD achieves superior detection performance and power efficiency.<p /><p>Language: en</p>",
language="en",
issn="1617-4909",
doi="10.1007/s00779-010-0292-x",
url="http://dx.doi.org/10.1007/s00779-010-0292-x"
}