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Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

The EEG signal is most useful for clinical diagnosis and in biomedical research. ElectroOculoGram (EOG), ElectroMyoGram (EMG) artifact are produced by eye movement and facial muscle movement respectively. An adaptive filtering method is proposed to remove these artifacts signals from EEG signals. Pr...

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Main Authors: Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.
Format: Conference or Workshop Item
Published: 2007
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.um.edu.my/9723/
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id my.um.eprints.9723
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spelling my.um.eprints.97232017-11-23T02:01:10Z http://eprints.um.edu.my/9723/ Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm Mehrkanoon, S. Moghavvemi, M. Fariborzi, H. TA Engineering (General). Civil engineering (General) The EEG signal is most useful for clinical diagnosis and in biomedical research. ElectroOculoGram (EOG), ElectroMyoGram (EMG) artifact are produced by eye movement and facial muscle movement respectively. An adaptive filtering method is proposed to remove these artifacts signals from EEG signals. Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. The real-time artifact removal is implemented by multi-channel Least Mean Square algorithm. The resulting EEG signals display an accurate and artifact free feature. 2007-11 Conference or Workshop Item PeerReviewed Mehrkanoon, S. and Moghavvemi, M. and Fariborzi, H. (2007) Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm. In: 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007, 25 - 28 November 2007, Kuala Lumpur, Malaysia.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Mehrkanoon, S.
Moghavvemi, M.
Fariborzi, H.
Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
description The EEG signal is most useful for clinical diagnosis and in biomedical research. ElectroOculoGram (EOG), ElectroMyoGram (EMG) artifact are produced by eye movement and facial muscle movement respectively. An adaptive filtering method is proposed to remove these artifacts signals from EEG signals. Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. The real-time artifact removal is implemented by multi-channel Least Mean Square algorithm. The resulting EEG signals display an accurate and artifact free feature.
format Conference or Workshop Item
author Mehrkanoon, S.
Moghavvemi, M.
Fariborzi, H.
author_facet Mehrkanoon, S.
Moghavvemi, M.
Fariborzi, H.
author_sort Mehrkanoon, S.
title Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
title_short Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
title_full Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
title_fullStr Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
title_full_unstemmed Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
title_sort real time ocular and facial muscle artifacts removal from eeg signals using lms adaptive algorithm
publishDate 2007
url http://eprints.um.edu.my/9723/
_version_ 1643688637876928512
score 13.160551

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