DocumentCode :
663130
Title :
EEG band powers for characterizing user engagement in P300-BCI
Author :
Yichuan Liu ; Ayaz, Hasan ; Onaral, B. ; Shewokis, P.A.
Author_Institution :
Sch. of Biomed. Eng., Drexel Univ., Philadelphia, PA, USA
fYear :
2013
fDate :
6-8 Nov. 2013
Firstpage :
1066
Lastpage :
1069
Abstract :
An asynchronous P300-based brain computer interface (BCI) allows users to operate the BCI at their own pace by being able to detect a user´s engagement. In our previous work, band powers has been shown to be able to provide additional information for characterizing user engagement and yielded better performance compared to the use of only the amplitudes of event-related potentials. In this follow up study, 19 subjects participated in an experiment which was designed to further evaluate additional predictors of user engagement using band powers. In addition to the regular P300 attended condition, two not-engaged conditions were considered: one with the P300 stimulus matrix still shown (control 1) and the other with stimulus covered by a blank screen (control 2). Alpha and beta band activities decreased in the order of control 2, control 1 and attended. Furthermore, the attended condition had lower delta activity compared to the control conditions. Classification results indicated that band powers were better at differentiating attended and control 2 conditions. Using band powers as additional features resulted in a moderate to moderately large (dz= 0.52 to 0.74) improvement over the classification of the two conditions.
Keywords :
brain-computer interfaces; electroencephalography; matrix algebra; medical signal processing; signal classification; EEG band powers; P300 stimulus matrix; P300-BCI; asynchronous P300-based brain computer interface; delta activity; user engagement characterization; user engagement detection; Band-pass filters; Biomedical engineering; Brain-computer interfaces; Educational institutions; Electroencephalography; Feature extraction; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location :
San Diego, CA
ISSN :
1948-3546
Type :
conf
DOI :
10.1109/NER.2013.6696121
Filename :
6696121
Link To Document :
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