DocumentCode :
2089405
Title :
A review on the current state of artifact removal methods for electroencephalogram signals
Author :
Rahman, Faridah Abd ; Othman, Mohd Fauzi ; Shaharuddin, Nurul Aimi
Author_Institution :
Centre for Artificial Intelligence and Robotics, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia (UTM), Kuala Lumpur, Malaysia
fYear :
2015
fDate :
May 31 2015-June 3 2015
Firstpage :
1
Lastpage :
6
Abstract :
Electroencephalograph (EEG) is a highly sensitive device and likely to be contaminated by undesirable non-cerebral potential called artifacts. Artifacts in EEG recordings is the major cause of reduced signal quality and can be caused by various factors such as blinks and eye movement, head movement, heartbeat and so on. The presence of the artifacts, which overlap with signal obtained from the brain, will make it difficult to analyze the information from EEG recordings and may lead to false interpretation of brain activity. In order to obtain such accurate and reliable signal information from EEG, the development of algorithms to identify and remove the artifacts from the signals is necessary. This paper reviews some of the current methods for artifact removal in EEG signals.
Keywords :
Adaptive filters; Electrocardiography; Electrodes; Electroencephalography; Electrooculography; Inference algorithms; Noise; adaptive filter; artifact removal; blind source separation (BSS); independent component analysis (ICA); regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (ASCC), 2015 10th Asian
Conference_Location :
Kota Kinabalu, Malaysia
Type :
conf
DOI :
10.1109/ASCC.2015.7244679
Filename :
7244679
Link To Document :
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