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

Saeid Mehrkanoon; Mahmoud Moghavvemi; Hossein Fariborzi

doi:10.1109/ICIAS.2007.4658583

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

Saeid Mehrkanoon, Mahmoud Moghavvemi, Hossein Fariborzi

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
Pages	1245-1250
Number of pages	6
DOIs	https://doi.org/10.1109/ICIAS.2007.4658583
State	Published - 2007
Event	2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 - Kuala Lumpur, Malaysia Duration: Nov 25 2007 → Nov 28 2007

Other

Other	2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
Country/Territory	Malaysia
City	Kuala Lumpur
Period	11/25/07 → 11/28/07

Keywords

EEG
EMG
EOG
Finite Impulse Response
Least Mean Square
Noise cancellation
Real-time -adaptive filter

ASJC Scopus subject areas

Artificial Intelligence
Control and Systems Engineering

Access to Document

10.1109/ICIAS.2007.4658583

Cite this

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title = "Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm",

abstract = "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.",

keywords = "EEG, EMG, EOG, Finite Impulse Response, Least Mean Square, Noise cancellation, Real-time -adaptive filter",

author = "Saeid Mehrkanoon and Mahmoud Moghavvemi and Hossein Fariborzi",

year = "2007",

doi = "10.1109/ICIAS.2007.4658583",

language = "English (US)",

isbn = "1424413559",

pages = "1245--1250",

booktitle = "2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007",

note = "2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 ; Conference date: 25-11-2007 Through 28-11-2007",

}

Mehrkanoon, S, Moghavvemi, M & 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., 4658583, pp. 1245-1250, 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007, Kuala Lumpur, Malaysia, 11/25/07. https://doi.org/10.1109/ICIAS.2007.4658583

Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm. / Mehrkanoon, Saeid; Moghavvemi, Mahmoud; Fariborzi, Hossein.
2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007. 2007. p. 1245-1250 4658583.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

AU - Mehrkanoon, Saeid

AU - Moghavvemi, Mahmoud

AU - Fariborzi, Hossein

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

KW - EEG

KW - EMG

KW - EOG

KW - Finite Impulse Response

KW - Least Mean Square

KW - Noise cancellation

KW - Real-time -adaptive filter

UR - http://www.scopus.com/inward/record.url?scp=57949088862&partnerID=8YFLogxK

U2 - 10.1109/ICIAS.2007.4658583

DO - 10.1109/ICIAS.2007.4658583

M3 - Conference contribution

AN - SCOPUS:57949088862

SN - 1424413559

SN - 9781424413553

SP - 1245

EP - 1250

BT - 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007

T2 - 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007

Y2 - 25 November 2007 through 28 November 2007

ER -

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

Abstract

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Keywords

ASJC Scopus subject areas

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