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A Falling Detection System with wireless sensor for the Elderly People Based on Ergnomics

원문정보

초록

영어

Fall detection is an important problem in the application research of wireless sensor. The paper presents wireless sensor architecture based human falling detection system especially for elderly people. The falling detection system is implemented using 3-axis acceleration sensor to measures and collects the elderly people activities acceleration and transfer data by zigbee-3G network to remote medical monitoring system platform, which makes a pre-processing method that suspected data is acquired based on one -class SVM classification algorithm. The algorithm analyzed different action which expended different threshold ranges of energy to judgment, and then analyzed the special temporal speed, displacement and angle as an auxiliary criterion for judgment. The experiments show that the application can offer a new guarantee for the elderly health.

목차

Abstract
 1. Introduction
 2. The Design of the Falling Detection Module
  2.1. The Overall Structure
  2.2. The Zigbee Network
  2.3. The 3-axis Acceleration Sensor
  2.4. Signal Preprocessing
 3. The Falling Detection Algorithm
  3.1. The Establishment of the Action Model
  3.2. The Algorithm Design
 4. Experiments and Result Analysis
 5. Conclusions
 References

저자정보

  • Zhenhe Ye College of Mechanical and Electrical Engineering, Agricultural University of HeBei, Baoding, HeBei, 071000, China
  • Ying Li College of Arts, Hebei Normal University of Science & Technology, Qinhuangdao, 066000, China
  • Qiaoxiang Zhao College of Arts, Hebei Normal University of Science & Technology, Qinhuangdao, 066000, China
  • Xue Liu School of Computer Science, Harbin University of Science and Technology, Harbin, HeiLongJiang, 150080, China

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