Title :
An ERP study on visual attention to facial stimuli; N170 component
Author :
Kafshgari, Narges Nourian ; Kahaki, Raheleh Davoodi ; Moradi, Mohammad Hassan ; Younesi, Ali
Author_Institution :
Dept. of Biomed. Eng., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
Attention to picture of face, particularly the human face is related to complex information processing in the brain. Humans pay more attention to human faces than other images. The purpose of this study is to verify the existence of particular attention to facial images and categorize the difference between attending to facial and non-facial images through a pair of different pictures as the targets. According to effects of visual stimuli such as color and luminance, the pictures modulated in greyscale (luminance-defined stimuli). Using a psychophysical task, EEG signals according to 10-20 standards in eight channels were recorded from 48 healthy volunteers. After the initial processing, ERP signal were elicited into two classes according to attention to the face and non-face images. In this study, the time window of the N170 component, was considered to extract new time features plus the N170 component; a negative peak in 170 milliseconds after stimulus onset. Optimum features were selected by t test criteria and classification was done by LDA, KNN and SVM classifiers. Validating the results was done by LOO cross validation criteria. Best result was obtained by SVM with 74.44% and was associated with frontal and parietal lobes.
Keywords :
bioelectric potentials; electroencephalography; face recognition; image classification; medical image processing; support vector machines; EEG signals; ERP signal; ERP study; KNN classifier; LDA classifier; LOO cross validation criteria; N170 component; SVM classifier; brain; complex information processing; facial stimuli; frontal lobe; greyscale; human face; luminance-defined stimuli; nonfacial images; parietal lobe; psychophysical task; visual attention; visual stimuli; Accuracy; Electrodes; Electroencephalography; Face; Face recognition; Feature extraction; Visualization; Attention; Classification; Event related potentials(ERP); N170; facial stimuli;
Conference_Titel :
Electrical Engineering (ICEE), 2014 22nd Iranian Conference on
Conference_Location :
Tehran
DOI :
10.1109/IranianCEE.2014.6999866