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Mobile phone-based pervasive fall detection

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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.

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Notes

  1. Jitterbug [39] is a cell phone service provider that is known for providing appealing cell phone and phone service to the elderly people [40].

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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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Authors and Affiliations

  1. Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing, 210096, China

    Jiangpeng Dai

  2. Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, 43210, USA

    Jiangpeng Dai, Xiaole Bai, Zhimin Yang & Dong Xuan

  3. Division of Physical Therapy, The Ohio State University, Columbus, OH, 43210, USA

    Zhaohui Shen

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  1. Jiangpeng Dai
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  2. Xiaole Bai
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  5. Dong Xuan
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Correspondence to Jiangpeng Dai.

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Dai, J., Bai, X., Yang, Z. et al. Mobile phone-based pervasive fall detection. Pers Ubiquit Comput 14, 633–643 (2010). https://doi.org/10.1007/s00779-010-0292-x

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