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A lamination-based piezoelectric insole gait analysis system for massive production for Internet-of-health things

Author

Listed:
  • Yanning Dai
  • Yuedong Xie
  • Junliang Chen
  • Shuaibo Kang
  • Lijun Xu
  • Shuo Gao

Abstract

Gait analysis has been proved to be a powerful and efficient means for health monitoring. Variety of nervous system diseases and emergencies can be detected by interpreting plantar stress distributions. Among gait analysis techniques, piezoelectric insole architectures receive boosting attentions due to its convenience for users to wear and its long-term and real-time monitoring ability. However, the complex integration of piezoelectric insole architecture limits its successful use for massive production for the Internet-of-health things (IoHT). Hence, in this article, we present a flexible printed circuit board and lamination-associated technique, which presents high detection sensitivity at 0.1 N, satisfying the need for assisting nervous system disease diagnosis, and showing strong potential for commercialization.

Suggested Citation

  • Yanning Dai & Yuedong Xie & Junliang Chen & Shuaibo Kang & Lijun Xu & Shuo Gao, 2020. "A lamination-based piezoelectric insole gait analysis system for massive production for Internet-of-health things," International Journal of Distributed Sensor Networks, , vol. 16(3), pages 15501477209, March.
    • Handle: RePEc:sae:intdis:v:16:y:2020:i:3:p:1550147720905431
    DOI: 10.1177/1550147720905431
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    Cited by:

    1. Li-Wei Chou & Jun-Hong Shen & Hui-Ting Lin & Yi-Tung Yang & Wen-Pin Hu, 2021. "A Study on the Influence of Number/Distribution of Sensing Points of the Smart Insoles on the Center of Pressure Estimation for the Internet of Things Applications," Sustainability, MDPI, vol. 13(5), pages 1-15, March.

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