Title :
Electrooculographic and electromyographic artifacts removal from EEG
Author :
Ferdousy, Rabeya ; Choudhory, Anisul Islam ; Islam, Md Shafiul ; Rab, Md Afzalur ; Chowdhory, Md Enamul Hoque
Author_Institution :
Dept. of Appl. Phys., Electron. & Commun. Eng., Univ. of Dhaka, Dhaka, Bangladesh
Abstract :
Completely automated methods for removing electroocular (EOG) and muscle (EMG) artifacts in the electroencephalogram (EEG) are presented in this paper which are implemented as an Automatic Artifact Removal (AAR) toolbox in EEGLAB. The method of removing EOG artifacts is based on second order blind identification (SOBI) as a blind source separation (BSS) technique and procedure of muscle artifact removal is based on canonical correlation analysis (CCA) as a blind source separation (BSS) technique. These techniques successfully deals with the removal of the most EOG and EMG artifacts in EEG recordings containing epilectic seizures without distorting the recorded ictal activity.
Keywords :
blind source separation; electro-oculography; electroencephalography; electromyography; medical signal processing; recording; signal denoising; EEG; EMG; EOG; blind source separation; canonical correlation analysis; electroencephalogram; electromyographic artifacts removal; electroocular artifacts; electrooculographic artifacts removal; muscle artifacts; second order blind identification; Electroencephalography; Electromyography; Electrooculography; Blind Source Separation (BSS); Canonical Correlation Analysis (CCA); Electroencephalogram (EEG); Electrooculography (EOG) and Electromyography (EMG); Second Order Blind Identification (SOBI);
Conference_Titel :
Chemical, Biological and Environmental Engineering (ICBEE), 2010 2nd International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8748-6
Electronic_ISBN :
978-1-4244-8749-3
DOI :
10.1109/ICBEE.2010.5651351
