Mobile phone-based pervasive fall detection

  • Authors:

  • Jiangpeng Dai;Xiaole Bai;Zhimin Yang;Zhaohui Shen;Dong Xuan

  • Affiliations:

  • Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing, China 210096 and Department of Computer Science and Engineering, The Ohio Stat ...;Department of Computer Science and Engineering, The Ohio State University, Columbus, USA 43210;Department of Computer Science and Engineering, The Ohio State University, Columbus, USA 43210;Division of Physical Therapy, The Ohio State University, Columbus, USA 43210;Department of Computer Science and Engineering, The Ohio State University, Columbus, USA 43210

  • Venue:
  • Personal and Ubiquitous Computing
  • Year:
  • 2010

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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 "baby boomers". 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.