Statistics Analysis and Eigenvalue Construction of EEG for Driving Fatigue by Fuzzy Entropy Arithmetic

摘要：

In this paper, electroencephalograms (EEG) of drivers driving under normal and fatigue state are collected and decomposed into 4 components, dl, d2, d3 and d4, by way of empirical mode decomposition (EMD). And Fuzzy Entropy arithmetic was used to analyze the characteristic of the components. Results show that fuzzy entropy ratio of d2 and d4 was able to distinguish the two types of EEG with a favorably agreed difference, which could decide whether or not the driver is in driving fatigue (DF).

关键词： electroencephalogram (EEG) driving fatigue(DF) empirical mode decomposition fuzzy entropy

作者: Mingen Zhong Junqiang Peng Hanchi Hong

作者单位: Department of Mechanical Engineering, Xiamen University of Technology, Xiamen Fujian, China School of Mechanical and Electronic Engineering, Tianjin Polytechnic University, Tianjin, China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronic & Mechanical Engineering and Information Technology(EMEIT 2011)(2011年机电工程与信息技术国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 3595-3598

在线出版日期: 2011-08-12（万方平台首次上网日期，不代表论文的发表时间）