Title :
A Novel Method to Remove Eye-Blink Artifacts Based on Correlation Using ICA
Author :
Hengsong Sheng ; Jin Xu ; Hongjun Tian
Author_Institution :
Key Lab. of Biomed. Inf. Eng. of Minist. of Educ., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
In this study a novel method is proposed to automatically remove eye-blink artifacts from EEG signals. EEG signals were first decomposed into independent components (ICs) by independent component analysis (ICA). Using temporal correlation theory, the sum of the correlation values between each IC and the EEG signals at some special electrodes was calculated, respectively. Consequently, all the correlation values were sorted by descending order. The ICs which have significantly bigger correlation than the other ICs were picked to set as eye-blink artifact components, which were then set as zero to reconstruct clean EEG signals. Finally, the proposed method was evaluated on some contaminated EEG signals. The experimental results show that it is able to effectively remove eye-blink artifacts with little distortion of underlying brain signals.
Keywords :
correlation theory; electroencephalography; independent component analysis; medical signal processing; signal reconstruction; EEG signal reconstruction; ICA; brain signal distortion; contaminated EEG signals; electrodes; eye-blink artifact components; eye-blink artifact removal method; independent component anlaysis; temporal correlation theory; Conferences; Internet; Social network services; Temporal correlation; eye-blink artifacts; independent component analysis (ICA);
Conference_Titel :
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location :
Beijing
DOI :
10.1109/GreenCom-iThings-CPSCom.2013.362