TY - GEN
T1 - Detection of the human-activity using the FCM
AU - Murakami, Junko
AU - Ito, Shin Ichi
AU - Mitsukura, Yasue
AU - Cao, Jianting
AU - Fukumi, Minoru
PY - 2007
Y1 - 2007
N2 - In this paper, we propose the detection system of the human activity by using the electroencephalograms (EEG). First, we measure the EEG data for subjects. In most of all conventional studies, the EEG having a lot of sensors is used. Therefore, subjects must eat or smoke while using the EEG interface. However, this situation is not practical for subjects. In this study, taking account of the burden of subjects, we use only one measurement point 'FP1'. First, we measure the EEG data and the EMG data for subjects. Then, the EEG feature is extracted by using the singular value decomposition (SVD). From the result, we classify the EEG pattern by the fuzzy C-means(FCM). If we cannot classify the EEG pattern into each activity, the discriminant analysis (DA) is used. We consider the EEG features of activities. Then, in order to show the effectiveness of the proposed method, computer simulations are done.
AB - In this paper, we propose the detection system of the human activity by using the electroencephalograms (EEG). First, we measure the EEG data for subjects. In most of all conventional studies, the EEG having a lot of sensors is used. Therefore, subjects must eat or smoke while using the EEG interface. However, this situation is not practical for subjects. In this study, taking account of the burden of subjects, we use only one measurement point 'FP1'. First, we measure the EEG data and the EMG data for subjects. Then, the EEG feature is extracted by using the singular value decomposition (SVD). From the result, we classify the EEG pattern by the fuzzy C-means(FCM). If we cannot classify the EEG pattern into each activity, the discriminant analysis (DA) is used. We consider the EEG features of activities. Then, in order to show the effectiveness of the proposed method, computer simulations are done.
KW - Discriminant analysis
KW - EEG
KW - FCM
KW - Human-activity
KW - Pattern recognition
KW - SVD
UR - http://www.scopus.com/inward/record.url?scp=48349133689&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48349133689&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2007.4406653
DO - 10.1109/ICCAS.2007.4406653
M3 - Conference contribution
AN - SCOPUS:48349133689
SN - 8995003871
SN - 9788995003879
T3 - ICCAS 2007 - International Conference on Control, Automation and Systems
SP - 1883
EP - 1887
BT - ICCAS 2007 - International Conference on Control, Automation and Systems
T2 - International Conference on Control, Automation and Systems, ICCAS 2007
Y2 - 17 October 2007 through 20 October 2007
ER -