A Plantar Inclinometer Based Approach to Fall Detection in Open Environments

  • Jianfei Sun
  • Zumin Wang
  • Liming Chen
  • Baofeng Wang
  • Changqing Ji
  • Shuai Tao
Part of the Studies in Computational Intelligence book series (SCI, volume 647)


In this paper, we report a threshold-based method of fall detection using plantar inclinometer sensor, which provides us the information of angle variations during walking, and of angle status after a fall. The angle variations and status are collected in three-dimensional space. We analyzed the normal range of angle variations during walking, and selected the thresholds by testing the distribution of plantar angles of falls. In the experiments, thresholds were selected from plantar angles of fall status in four directions: forward, backward, left and right. Using the selected thresholds, we detected falls of five subjects in different situations for five hundred times and obtained the average detection rate of 85.4 %.


Sensor Module Angle Variation Fall Detection Subsequent Injury Privacy Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the National Natural Science Foundation of China (Grant No. 61501076)


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jianfei Sun
    • 1
  • Zumin Wang
    • 1
  • Liming Chen
    • 2
  • Baofeng Wang
    • 1
  • Changqing Ji
    • 1
  • Shuai Tao
    • 1
  1. 1.Information and Engineering CollegeDalian UniversityDalianChina
  2. 2.School of Computer Science and InformaticsDe Montfort UniversityLeicesterUK

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