eprintid: 8057
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/80/57
datestamp: 2023-11-09 16:19:54
lastmod: 2023-11-09 16:19:54
status_changed: 2023-11-09 16:11:41
type: conference_item
metadata_visibility: show
creators_name: Egambaram, A.
creators_name: Badruddin, N.
creators_name: Asirvadam, V.S.
creators_name: Begum, T.
creators_name: Fauvet, E.
creators_name: Stolz, C.
title: Variance thresholded EMD-CCA technique for fast eye blink artifacts removal in EEG
ispublished: pub
keywords: Electroencephalography; Real time control; Signal processing, Canonical correlation analysis; Electroencephalogram signals; Empirical Mode Decomposition; Eye-blink artifacts; Hybrid algorithms; Real-time implementations; Threshold algorithms; Variance Threshold, Signal to noise ratio
note: cited By 2; Conference of 2017 IEEE Region 10 Conference, TENCON 2017 ; Conference Date: 5 November 2017 Through 8 November 2017; Conference Code:133992
abstract: Eye blink (EB) artifacts generated during eye blinks often contaminate electroencephalogram (EEG) signal. Previously Empirical Mode Decomposition (EMD) and Canonical Correlation Analysis (CCA), hybrid EMD-CCA were developed for EB artifact removal in EEG. However, EMD restricts the hybrid algorithm for real time implementation due to its slow processing nature, hence the algorithm has to be enhanced so that it can be a viable solution for real-time EB artifact removal. In this research work, to avoid applying EMD repetitively as and when EB artifacts occur, a method to use EMD minimally is approached. A suitable EB artifact region is detected through a variance threshold algorithm. This region is then subjected to EMD, where an EB artifact template is extracted out. This template is used by CCA to remove all EB artifacts that are present in that particular EEG signal, avoiding the need to apply EMD repetitively. The proposed method, (varEMD-CCA) is analyzed in terms of Signal-to-Noise Ratio (SNR) and the time consumed in removing EB artifacts from the entire length of the frontal channel, Fp1 of the EEG signal. Analysis shows that the proposed method (varEMD-CCA) is at least 40 times faster than the previous EMD-CCA method. The SNR of both methods are also comparable, which means the proposed method could comparably removes EB artifacts as the previous method does. © 2017 IEEE.
date: 2017
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044193230&doi=10.1109%2fTENCON.2017.8228293&partnerID=40&md5=d2a03e2c168ee12cbd7138e572d47132
id_number: 10.1109/TENCON.2017.8228293
full_text_status: none
publication: IEEE Region 10 Annual International Conference, Proceedings/TENCON
volume: 2017-D
pagerange: 2560-2565
refereed: TRUE
isbn: 9781509011339
issn: 21593442
citation:   Egambaram, A. and Badruddin, N. and Asirvadam, V.S. and Begum, T. and Fauvet, E. and Stolz, C.  (2017) Variance thresholded EMD-CCA technique for fast eye blink artifacts removal in EEG.  In: UNSPECIFIED.