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

fYear

2009

fDate

April 29 2009-May 2 2009

Firstpage

136

Lastpage

139

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/NER.2009.5109253

Filename

5109253