We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
The week's pick
Responsive image
An Efficient Restoration Method for the Faint Dot Matrix Images

Ao Zhu Peng Cao
Random Articles
Reseach Article

Artifact Removal from EEG Signals

by A. Guruva Reddy, Srilatha Narava
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 13
Year of Publication: 2013
Authors: A. Guruva Reddy, Srilatha Narava
10.5120/13543-1175

A. Guruva Reddy, Srilatha Narava . Artifact Removal from EEG Signals. International Journal of Computer Applications. 77, 13 ( September 2013), 17-19. DOI=10.5120/13543-1175

@article{ 10.5120/13543-1175,
author = { A. Guruva Reddy, Srilatha Narava },
title = { Artifact Removal from EEG Signals },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 13 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 17-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number13/13543-1175/ },
doi = { 10.5120/13543-1175 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:50:09.644006+05:30
%A A. Guruva Reddy
%A Srilatha Narava
%T Artifact Removal from EEG Signals
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 13
%P 17-19
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Electroencephalographic (EEG) recordings are often contaminated with several artifacts. Powerline interference and baseline noise is always present in EEG response of every patient. A number of strategies are available to deal with noise effectively both at the time of EEG recording as well as during preprocessing of recorded data. The aim of the paper is to give an overview of the most common sources of noise and review methods for prevention and removal of noise in EEG recording ,including elimination of noise sources.

References
  1. M. Ferdjallah and R. E. Barr "Adaptive Digital Notch Filter Design on the Unit Circle for the Removal of Powerline Noise from Biomedical Signals", IEEE Trans. on Biomedical Engineering
  2. M. V. Dragosevic, and S. S. Stankovic "An Adaptive Notch Filter with Improved Tracking Properties", IEEE Trans. Signal Processing, vol. 43, no. 9, pp. 2068–2078.
  3. He P, Wilson G, Russel C: Removal of artifacts from electro-encephalogram by adaptive filtering. Medical & biological engineering & computing 2004; 42(3): 407-12.
  4. R. H. Kwong, and E. W. Johnston "A Variable Step Size LMS Algorithm", IEEE Trans. Signal Processing, vol. 40, no. 7, pp. 1633–1642, 1992.
  5. Haykin, Simon, 2001, "Adaptive Filter Theory", ISBN-10: 0130901261, Prentice-Hall, pp. 231-38, 320-24.
  6. MIT-BIH arrhythmia database, Http://www. physionet. org/phsiobank/database/mitdb/
  7. Haykin, Simon, 2003, "Least-Mean-Square Adaptive Filters", ISBN 0-471-21570-8 Wiley, pp. 315.
  8. Honing. M. ,Messerschmitt. D, 1984, "Adaptive Filters: Structures, Algorithmsand Applications", ISBN-13: 978-0898381634, Kluwer Academic Publishers,
Index Terms

Computer Science
Information Sciences

Keywords

Artifact Electroencephalogram Line interference.

Powered by PhDFocusTM