Biorthogonal wavelet for EEG signal compression

Authors:
A. Bousbia-Salah;M. A. Ait-Ameur;M. Talha-Kedir
Affiliations:
University of Sciences and Technology Houari Boumédiène, Algiers, Algeria;University of Sciences and Technology Houari Boumédiène, Algiers, Algeria;University of Sciences and Technology Houari Boumédiène, Algiers, Algeria
Venue:
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Year:
2011

Citing 2
Cited 0

Data compression methods for EEG

Technology and Health Care
De-noising by soft-thresholding

IEEE Transactions on Information Theory

Quantified Score

Hi-index	0.00

Visualization

Abstract

Compression of EEG signals is gaining importance in biomedical engineering due to the potential applications in telemedicine. In this paper, we propose a signal compression electro-encephalographic (EEG) method based on discrete wavelet transform (DWT). In order to do this, we developed an algorithm that makes the compression and recovery of these signals using the best suited method, the biorthogonal wavelet. The implementation of this algorithm on real signals (normal and pathological) gave satisfactory compression rates ranging from 65% to 90%, ensuring a good recovery.