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Personal and Ubiquitous Computing

, Volume 14, Issue 7, pp 633–643 | Cite as

Mobile phone-based pervasive fall detection

  • Jiangpeng Dai
  • Xiaole Bai
  • Zhimin Yang
  • Zhaohui Shen
  • Dong Xuan
Original Article

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.

Keywords

Pervasive fall detection Mobile phones Context information Accelerometer Magnetic field sensor Accessory 

Notes

Acknowledgments

This work was supported in part by the US National Science Foundation (NSF) under grants No. CNS-0916584, CAREER Award CCF-0546668, and the Army Research Office (ARO) under grant No. AMSRD-ACC-R50521-CI. Any opinions, findings, conclusions, and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.

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Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Jiangpeng Dai
    • 1
    • 2
  • Xiaole Bai
    • 2
  • Zhimin Yang
    • 2
  • Zhaohui Shen
    • 3
  • Dong Xuan
    • 2
  1. 1.Key Laboratory of Computer Network and Information Integration, Ministry of EducationSoutheast UniversityNanjingChina
  2. 2.Department of Computer Science and EngineeringThe Ohio State UniversityColumbusUSA
  3. 3.Division of Physical TherapyThe Ohio State UniversityColumbusUSA

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