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Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram

Abd Rahman, Faridah and Othman, Mohd Fauzi and Hamzah, Mohd Ilham Rusydan Hamzah (2018) Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram. In: International Conference on Computer and Communication Engineering (ICCCE), 19th-20th September 2018, Kuala Lumpur.

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Abstract

The interference of eye blink artifacts can cause serious distortion to electroencephalogram (EEG) which could bias the signal interpretation and reduce the classification accuracy in a brain-computer interface (BCI) application. To overcome this problem, an algorithm to automatically detect and remove the artifacts from EEG signals is highly desirable. One of the methods that can be applied for automatic artifacts removal is adaptive filtering through an adaptive noise cancellation (ANC) system. In this paper, we compare the performance of three adaptive algorithms; namely LMS, RLS, and ANFIS, in removing the eye blink from EEG signals. To evaluate the results, the SNR, MSE and correlation coefficient values are calculated based on the results obtained by using one of the widely used methods for blinks removal, independent component analysis (ICA). The results show that RLS algorithm provides the best performance when comparing with the ICA method.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 8148/70296
Uncontrolled Keywords: adaptive filter, electroencephalogram (EEG), eye blink artifacts, LMS, RLS, ANFIS
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication. Including telegraphy, radio, radar, television
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Kulliyyah of Engineering
Depositing User: Faridah Abd Rahman
Date Deposited: 19 Feb 2019 16:30
Last Modified: 19 Feb 2019 16:30
URI: http://irep.iium.edu.my/id/eprint/70296

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