Preprocessing of Electrical Activity in the Brain

Authors

  • G. Chekhmane Department of Biomedical Engineering, University of Tlemcen, Algeria
  • R. Benali Department of Biomedical Engineering, University of Tlemcen, Algeria https://orcid.org/0000-0002-5648-1718

DOI:

https://doi.org/10.26713/jims.v13i3.2055

Abstract

Electroencephalography (EEG) is the most effective tool to diagnosis of epileptic diseases. It provides a signal indicated the electrical activity of the brain, which is contaminated by different sources of artefacts and noises. This paper presents a method for removing ocular (EOG) and muscular (EMG) artefacts in the EEG records. The threshold denoising method based on the stationary wavelet transform (SWT) was used to remove these artifacts. The main objective is to improve the quality of the signal in terms of performance like signal to noise ratio (SNR), correlation coefficient (CC), mean squared error (MSE) and distortion coefficients (THD). As results, different types of thresholding and mother wavelets were in consideration and it was revealed that Daubechies along with the soft thresholding technique and four level of decomposition are better for a higher SNR and correlation coefficient thus decreasing the mean squared error and distortion factor so, these results improve the validity of the proposed technique.

Downloads

Download data is not yet available.

Downloads

Published

2022-09-18
CITATION

How to Cite

Chekhmane, G., & Benali, R. (2022). Preprocessing of Electrical Activity in the Brain. Journal of Informatics and Mathematical Sciences, 13(3), 149–156. https://doi.org/10.26713/jims.v13i3.2055

Issue

Vol. 13 No. 3 (2021)

Section

Research Articles

License

Authors who publish with this journal agree to the following terms:
  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a CCAL that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.