An Environmental-Adaptive Fall Detection System on Mobile Device

  • Authors:

  • Sung-Yen Chang;Chin-Feng Lai;Han-Chieh Josh Chao;Jong Hyuk Park;Yueh-Min Huang

  • Affiliations:

  • Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan 701;Institute of Computer Science and Information Engineering, National ILan University, I-Lan, Taiwan 260;Institute of Computer Science and Information Engineering, National ILan University, I-Lan, Taiwan 260;Department of Computer Science and Engineering, Seoul National University of Technology, Seoul, Korea 139-742;Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan 701

  • Venue:
  • Journal of Medical Systems
  • Year:
  • 2011

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Abstract

When facing damages caused by falls, a well designed smart sensor system to detect falls can be both medically and economically helpful. This research introduces a portable terrain adaptable fall detection system, by placing accelerometers and gyroscopes in parts of the body and transmit data through wireless transmitter modules to mobile devices to get the related information and combining it with the center of gravity clustering algorithm introduced in this research which computes the human body behavior patterns according the relationship between the center of gravity in the body and the feet portion of the body. Compared with the research in the past, this system is not only highly accurate and robust, but also able to adapt to different types of terrains, which solves the problems that other researches have for detection errors when the client is climbing the stairs or walking on a slant.