TY - GEN
T1 - EEG based patient emotion monitoring using relative wavelet energy feature and Back Propagation Neural Network
AU - Purnamasari, Prima Dewi
AU - Ratna, Anak Agung Putri
AU - Putro, Benyamin Kusumo
PY - 2015/11/4
Y1 - 2015/11/4
N2 - In EEG-based emotion recognition, feature extraction is as important as the classification algorithm. A good choice of features results in higher recognition rate. However, there is no standard method for feature extraction in EEG-based emotion recognition, especially for real time monitoring, where speed of computation is crucial. In this work, we assess the use of relative wavelet energy as features and Back Propagation Neural Network (BPNN) as classifier for emotion recognition. This method was implemented in simulated real time emotion recognition by using a publicly accessible database. The results showed that relative wavelet energy and BPNN achieved an average recognition rate of 92.03%. The highest average recognition rate was achieved when the time window was 30s.
AB - In EEG-based emotion recognition, feature extraction is as important as the classification algorithm. A good choice of features results in higher recognition rate. However, there is no standard method for feature extraction in EEG-based emotion recognition, especially for real time monitoring, where speed of computation is crucial. In this work, we assess the use of relative wavelet energy as features and Back Propagation Neural Network (BPNN) as classifier for emotion recognition. This method was implemented in simulated real time emotion recognition by using a publicly accessible database. The results showed that relative wavelet energy and BPNN achieved an average recognition rate of 92.03%. The highest average recognition rate was achieved when the time window was 30s.
KW - brain wave
KW - EEG
KW - emotion monitoring
KW - emotion recognition
KW - wavelet energy
UR - http://www.scopus.com/inward/record.url?scp=84953288176&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2015.7318978
DO - 10.1109/EMBC.2015.7318978
M3 - Conference contribution
C2 - 26736878
AN - SCOPUS:84953288176
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2820
EP - 2823
BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Y2 - 25 August 2015 through 29 August 2015
ER -