Wearable Devices for Fall Detection of Human Body

Yan-Cheng Chen1, Shiannfong Huang2, Shu-Hsien Liao1, Zhe-Yu Li3

  • 1National Taiwan Normal University
  • 2Oriental Institute of Technology
  • 3National Yunlin University of Science and Technology

Details

13:25 - 14:15 | Thu 16 Feb | Ballroom D | ThRPF.22

Session: Rapid Fire Session 02: Sensor Informatics I

Abstract

This study on the utilization of parameters focuses on detecting the human body falling. It explores how to prevent falls and fall alarms. A sensor detects a three-axis acceleration distribution pattern to determine whether a fall took place. Users can set up their behaviors of standing, sitting down, walking, turning around, etc., in daily life. The resultant data will promote the degree of discrimination of each user and the related data will be sent to the back-end medical personnel prior to providing appropriate personal healthcare if it is required.