Title :
Combination of independent component analysis and feature extraction of ERP for level classification of sustained attention
Author :
Ghassemi, Farnaz ; Moradi, Mohammad Hasan ; Doust, Mahdi Tehrani ; Abootalebi, Vahid
Author_Institution :
Biomed. Eng. Fac. of Amirkabir, Univ. of Technol., Tehran, Iran
fDate :
April 29 2009-May 2 2009
Abstract :
This paper investigates the relations between ERP features and visual sustained attention. Continuous Performance Test is used for determining sustained attention level. Fifty eight features were extracted from the 19-channel recorded signals. Twenty four subjects were divided into three classes according to their attention level. LDA classifier is used and high accuracy (94%, 88% and 93% for each two classes) is achieved by using two features in classifying the test data. Obtained results are in agreement with the previous studies.
Keywords :
cognition; electroencephalography; feature extraction; medical signal processing; neurophysiology; pattern classification; signal classification; visual evoked potentials; EEG 19-channel recorded signal; ERP feature extraction; LDA classifier; electroencephalography; event related potential continuous performance test; visual sustained attention; Biomedical engineering; Biomedical measurements; Brain; Electroencephalography; Enterprise resource planning; Feature extraction; Independent component analysis; Linear discriminant analysis; Neural engineering; Testing; Event Related Potential; Independent Component Analysis; LDA Classifier; Sustained Attention;
Conference_Titel :
Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-2072-8
Electronic_ISBN :
978-1-4244-2073-5
DOI :
10.1109/NER.2009.5109253
