Feature extraction of EEG signals using power spectral entropy

	Feature extraction of EEG signals using power spectral entropy
	Zhang, Aihua; Yang, Bin; Huang, Ling
	2008
页码	435-+
英文摘要	Brain-Computer Interfaces (BCI) use electroencephalography (EEG) signals recorded from the scalp to create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. One of the most important components of BCI is feature extraction of EEG signals. How to rapidly and reliably extract EEG features for expressing the brain states Of different mental tasks is the crucial element for exact classification. This paper presents an approach that performs EEG feature extraction during imagined right and left hand movements by using power spectral entropy (PSE). It acquires good classification results with the time-variable linear classifier. The maximal accuracy achieves 90% The results show that the PSE is a sensitive parameter for EEG of imaginary hand movements. The method is simple and quick and it provides a promising method for on-line BCI system.
会议录	BMEI 2008: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOL 2
会议录出版者	IEEE COMPUTER SOC
会议录出版地	10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
语种	英语
资助项目	National Natural Science Foundation of China[30670529] ; Chunhui Plan of Ministry of Education of China[Z2005-2-62007]
WOS研究方向	Engineering ; Mathematical & Computational Biology ; Instruments & Instrumentation ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000257001500087
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/37969]
专题	电气工程与信息工程学院
通讯作者	Zhang, Aihua
作者单位	Lanzhou Univ Technol, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Aihua,Yang, Bin,Huang, Ling. Feature extraction of EEG signals using power spectral entropy[C]. 见:.