Conference Paper2017

Effect of EMG artifacts on video category classification from EEG

Mohammad Raihanul Bashar, Rayhan Sardar Tipu, Aunnoy K Mutasim, M Ashraful Amin

2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology (ICIEV-ISCMHT)

IEEE, pp. 1–4

DOI: 10.1109/iciev.2017.8338603URL

Abstract

EEG (electroencephalography) signals are highly susceptible to noise. Mixture of artifacts like EOG (electrooculography) and EMG (electromyography) with the EEG signals are inevitable. In this paper, we present our findings of the effects of EMG artifacts on EEG signals to categorize videos. The experiments suggest that for video category classification using EEG, signals with EMG artifacts have more discriminating capacity.

Keywords

  • EMG artifacts
  • Electrooculography
  • EEG signals
  • EEG classification

CCDS Authors

Mohammad Raihanul Bashar
Mohammad Raihanul Bashar

Mohammad Raihanul Bashar

  • Alumni, CCDS

  • PhD Student

    Concordia University, Canada

  • BSc

    Independent University, Bangladesh (IUB)

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, Pattern Recognition, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

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