TY - GEN
T1 - Subject-specific channel selection for classification of motor imagery electroencephalographic data
AU - Yang, Yuan
AU - Kyrgyzov, Olexiy
AU - Wiart, Joe
AU - Bloch, Isabelle
PY - 2013/10/18
Y1 - 2013/10/18
N2 - Brain-computer interfaces (BCIs) are systems that record brain signals and then classify them to generate computer commands. Keeping a minimal number of channels (electrodes) is essential for developing portable BCIs. Unlike existing methods choosing channels without optimization of time segment for classification, this work proposes a novel subject-specific channel selection method based on a criterion derived from Fisher's discriminant analysis to realize the parametrization of both time segment and channel positions. The experimental results show that the method can efficiently reduce the number of channels (from 118 channels to no more than 11), and shorten the training time, without a significant decrease of classification accuracy on a standard dataset.
AB - Brain-computer interfaces (BCIs) are systems that record brain signals and then classify them to generate computer commands. Keeping a minimal number of channels (electrodes) is essential for developing portable BCIs. Unlike existing methods choosing channels without optimization of time segment for classification, this work proposes a novel subject-specific channel selection method based on a criterion derived from Fisher's discriminant analysis to realize the parametrization of both time segment and channel positions. The experimental results show that the method can efficiently reduce the number of channels (from 118 channels to no more than 11), and shorten the training time, without a significant decrease of classification accuracy on a standard dataset.
KW - biomedical signal processing
KW - Brain computer interfaces
KW - electroencephalography
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=84890444321&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890444321&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6637856
DO - 10.1109/ICASSP.2013.6637856
M3 - Conference contribution
AN - SCOPUS:84890444321
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1277
EP - 1280
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -