Title :
Classification for Different Mental Tasks Based on EEG Signals
Author_Institution :
Dept. of Comput. Sci., Weinan Teachers Univ., Weinan, China
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;
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
DOI :
10.1109/ICEE.2010.955
