EEG Feature Extraction During Mental Fatigue and Relaxation by Principal Component Analysis

摘要：

EEG is one of the most predictive and reliable measurements for mental fatigue and relaxation evaluation. The aim of this study is to transform a number of EEG spectrum variables into few principal components using PCA method. After transformation, EEG multivariate dataset can be visualized in a lower-dimensional space where different mental states are clearly discriminated from each other.

关键词： Mental fatigue Relaxation EEG feature extraction PCA

作者: Lan-Lan Chen Jun-Zhong Zou Jian Zhang Chun-Mei Wang Min Wang

作者单位: Department of Automation, East China University of Science and Technology, Shanghai 200237, China

会议类型: 国际会议

会议名称: The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)

会议地点: 杭州

会议语种:英文

页码: 371-374

在线出版日期: 2009-11-15（万方平台首次上网日期，不代表论文的发表时间）