TY  - CONF
ID  - SisLab2593
UR  - http://atc-conf.org
A1  - Pham Van, Thanh
A1  - Dang Nhu, Dinh
A1  - Nguyen Duc, Anh
A1  - Nguyen Tien, Anh
A1  - Chu Duc, Hoang
A1  - Tran, Duc Tan
Y1  - 2017/10/18/
N2  - Electrooculography (EOG) artifacts, generated by winking or other eye?s movements, should be eliminated because they are the cause of the wrong decision in analysis the Electroencephalography (EEG) data, especially in the diagnosis of epilepsy. One of the efficient methods for signal separation is the Second order blind identification (SOBI), a blind source separation technique. In most cases, the activities of the two eyes are the same, and SOBI identify that there is only one source of artifact. However, in some cases, the activities of the two eyes are different, and SOBI identify that there are two different sources of artifacts [1]. The problem is that SOBI cannot provide the information about the order of sources. It means that, it cannot point out how many sources of EOG. It would lead to the wrong decision in EEG analysis. To solve this current limitation, in this paper, we propose an effective method to remove EOG from EEG using SOBI combined with intelligent source identification technique. The proposed method was evaluated carefully using experimental data. It determined successfully the number of EOG sources and removes these artifacts more accurately and efficiently.
TI  - Automatic removal of EOG artifacts using SOBI algorithm combined with intelligent source identification technique
SP  - 260
M2  - Quy Nhon, Viet Nam
AV  - public
EP  - 264
T2  - International Conference on Advanced Technologies for Communications
ER  -