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An adaptive multi-level wavelet denoising method for 40-Hz ASSR

Authors :
Dimitrios Hatzinakos
Sahar Javaher Haghighi
Hossam El-Beheiry
Wael Louis
Source :
ICASSP
Publication Year :
2016
Publisher :
IEEE, 2016.

Abstract

This paper presents a novel method for extracting auditory steady state response (ASSR) signals from background electroencephalogram. 40-Hz ASSR signals are sensitive to subject's state of consciousness and can be used as a monitor for the depth of anaesthesia. The suggested method is a multilevel adaptive wavelet denoising scheme that extracts ASSR cycles faster than the currently used averaging schemes and can monitor depth of anesthesia with minimum delay. It estimates the variance of noise and adapts the threshold at each denoising level. The algorithm benefits from the fact that wavelet transform preserves temporality and takes into consideration the correlation of the neighbor wavelet coefficients. Our method extracts ASSR from small number of epochs in a short time moreover, it does not neglect the variations of the signal from one epoch to the other and outperforms averaging. The performance of the proposed scheme is evaluated on the synthetic and on real data recorded during induction of anaesthesia ASSR signals in the paper.

Details

Database :
OpenAIRE
Journal :
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Accession number :
edsair.doi...........169fcbbdd571a8ad64d5f15e4b9fb07f
Full Text :
https://doi.org/10.1109/icassp.2016.7471790