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

Saeid Mehrkanoon, Mahmoud Moghavvemi, Hossein Fariborzi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 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 languageEnglish (US)
Title of host publication2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
Pages1245-1250
Number of pages6
DOIs
StatePublished - 2007
Event2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 - Kuala Lumpur, Malaysia
Duration: Nov 25 2007Nov 28 2007

Other

Other2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
CountryMalaysia
CityKuala Lumpur
Period11/25/0711/28/07

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

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