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计算机工程 ›› 2012, Vol. 38 ›› Issue (11): 271-273.doi: 10.3969/j.issn.1000-3428.2012.11.082

• 开发研究与设计技术 • 上一篇    下一篇

基于步态加速度特征的人体疲劳检测

李月香，李美俊，范小芹   

  1. (山西大学计算机与信息技术学院，太原 030006)
  • 收稿日期:2011-11-08 出版日期:2012-06-05 发布日期:2012-06-05
  • 作者简介:李月香(1958－)，女，副教授，主研方向：嵌入式系统；李美俊，硕士研究生；范小芹，副教授、博士
  • 基金项目:
    国家自然科学基金资助项目(61100058)

Human Fatigue Detection Based on Gait Acceleration Feature

LI Yue-xiang, LI Mei-jun, FAN Xiao-qin   

  1. (School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China)
  • Received:2011-11-08 Online:2012-06-05 Published:2012-06-05

PDF

1044

被引次数

10

摘要： 传统基于生理学的人体疲劳检测方法存在周期较长、准确度较低的问题。为此，提出一种基于步态加速度特征的人体疲劳状态检测方法。通过微机电传感器加速度计采集被检测人的步态加速度数据，给出基于相关系数法的步态疲劳状态阈值判断方法。实验结果表明，9个样本的检测准确率为93.06%，准确率较高，时间复杂度较低。

关键词: 步态加速度, 人体疲劳, 相关系数法, 微机电传感器

Abstract: Traditional physiology human fatigue detection methods have the problems that the time is long and accuracy is low. Aiming at this problem, this paper proposes a novel method for human fatigue identification based on gait acceleration. Collecting gait acceleration data by using a Micro Electro Mechanical Sensor(MEMS) triaxial accelerometer, based on correlation coefficients, the method proposed in this paper can be used to identify human fatigue. Experimental results show that the accuracy of identification is 93.06% with 9 test subjects, and this method has the advantages of calculating time and accuracy.

Key words: gait acceleration, human fatigue, correlation coefficient method, Micro Electro Mechanical Sensor(MEMS)

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