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A Plantar Inclinometer Based Approach to Fall Detection in Open Environments

  • Jianfei Sun
  • , Zumin Wang
  • , Liming Chen
  • , Baofeng Wang
  • , Changqing Ji
  • , Shuai Tao

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

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 %.
Original languageEnglish
Title of host publicationEmerging Trends and Advanced Technologies for Computational Intelligence
PublisherSpringer Cham
Pages1-13
Volume647
ISBN (Print)978-3-319-33351-9
DOIs
Publication statusPublished (in print/issue) - 7 Jun 2016

Publication series

NameEmerging Trends and Advanced Technologies for Computational Intelligence
Volume647
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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