DocumentCode
2419097
Title
Classification for Different Mental Tasks Based on EEG Signals
Author
Jia, Hua-Ping
Author_Institution
Dept. of Comput. Sci., Weinan Teachers Univ., Weinan, China
fYear
2010
fDate
7-9 May 2010
Firstpage
3811
Lastpage
3814
Abstract
Electroencephalogram(EEG) signal is an important information source of underlying brain processes. The communication based on EEG between human brain and computer is a new modality of human-computer interaction. Through time-domain regression method for EEG denoising pretreatment, AR model coefficient is extracted as feature vector, classifies the mental tasks based on BP network and PNN network.
Keywords
backpropagation; brain-computer interfaces; electroencephalography; feature extraction; human computer interaction; regression analysis; AR model coefficient; BP network; EEG signal; brain processes; electroencephalogram signal; feature extraction; human computer interaction; time domain regression method; Brain modeling; Classification algorithms; Electroencephalography; Feature extraction; Hidden Markov models; Integrated circuits; Mathematical model; AR model; BP network; EEG; PNN network; feature extraction;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-0-7695-3997-3
Type
conf
DOI
10.1109/ICEE.2010.955
Filename
5591803
Link To Document