TY - GEN
T1 - Classification improvement of P300 response based auditory spatial speller brain-computer interface paradigm
AU - Chang, Moonjeong
AU - Makino, Shoji
AU - Rutkowski, Tomasz M.
PY - 2013
Y1 - 2013
N2 - The aim of the presented study is to provide a comprehensive test of the EEG evoked response potential (ERP) feature selection techniques for the spatial auditory BCI-speller paradigm, which creates a novel communication option for paralyzed subjects or body-able individuals requiring a direct brain-computer interfacing application. For rigor, the study is conducted with 16 BCI-naive healthy subjects in an experimental setup based on five Japanese hiragana characters in an offline processing mode. In our previous studies the spatial auditory stimuli related P300 responses resulted with encouragingly separable target vs. non-target latencies in averaged responses, yet that finding was not well reproduced in the online BCI single trial based settings. We present the case study indicating that the auditory spatial unimodal paradigm classification accuracy can be enhanced with an AUC based feature selection approach, as far as BCI-naive healthy subjects are concerned.
AB - The aim of the presented study is to provide a comprehensive test of the EEG evoked response potential (ERP) feature selection techniques for the spatial auditory BCI-speller paradigm, which creates a novel communication option for paralyzed subjects or body-able individuals requiring a direct brain-computer interfacing application. For rigor, the study is conducted with 16 BCI-naive healthy subjects in an experimental setup based on five Japanese hiragana characters in an offline processing mode. In our previous studies the spatial auditory stimuli related P300 responses resulted with encouragingly separable target vs. non-target latencies in averaged responses, yet that finding was not well reproduced in the online BCI single trial based settings. We present the case study indicating that the auditory spatial unimodal paradigm classification accuracy can be enhanced with an AUC based feature selection approach, as far as BCI-naive healthy subjects are concerned.
UR - http://www.scopus.com/inward/record.url?scp=84894329063&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894329063&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2013.6718454
DO - 10.1109/TENCON.2013.6718454
M3 - Conference contribution
AN - SCOPUS:84894329063
SN - 9781479928262
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
BT - 2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Conference Proceedings
T2 - 2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013
Y2 - 22 October 2013 through 25 October 2013
ER -