TY - GEN
T1 - Functional near infrared spectroscopy based congitive task classification using support vector machines
AU - Abibullaev, Berdakh
AU - Kang, Won Seok
AU - Lee, Seung Hyun
AU - An, Jinung
PY - 2010/7/16
Y1 - 2010/7/16
N2 - the present study analyzes brain hemodynamic concentration of frontal cortex during four cognitive mental tasks. The analysis procedure consists of three sequential steps. First, the strong brain activation regions have been investigated thoroughly from all subjects in order to And a proper electrode location that generates important brain stimuli. Second, a feature extraction method that is based on wavelet transforms and denoising technique for extraction of important task-relevant features. Finally, support vector machines have been using in the classification of mental tasks with wavelet input coefficients. By applying the methodology for 4-subjects in average we achieved 92 % classification rates. However, the results depend on the type of the task that subject were performing. It is expect that the proposed method can be a basic technology for brain-computer interface by combining wavelets with support vector machines.
AB - the present study analyzes brain hemodynamic concentration of frontal cortex during four cognitive mental tasks. The analysis procedure consists of three sequential steps. First, the strong brain activation regions have been investigated thoroughly from all subjects in order to And a proper electrode location that generates important brain stimuli. Second, a feature extraction method that is based on wavelet transforms and denoising technique for extraction of important task-relevant features. Finally, support vector machines have been using in the classification of mental tasks with wavelet input coefficients. By applying the methodology for 4-subjects in average we achieved 92 % classification rates. However, the results depend on the type of the task that subject were performing. It is expect that the proposed method can be a basic technology for brain-computer interface by combining wavelets with support vector machines.
KW - BCI
KW - Component
KW - Functional near-infrared spectroscopy
KW - Mental task classification
KW - Support vector machines
KW - Wavelets
UR - http://www.scopus.com/inward/record.url?scp=77954476071&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954476071&partnerID=8YFLogxK
U2 - 10.1109/HIBIT.2010.5478913
DO - 10.1109/HIBIT.2010.5478913
M3 - Conference contribution
AN - SCOPUS:77954476071
SN - 9781424459704
T3 - 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010
SP - 7
EP - 12
BT - 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010
T2 - 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010
Y2 - 20 April 2010 through 22 April 2010
ER -