Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses

Arnaud Jacquin, Elvir Causevic, Roy John, Jelena Kovacevic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a new method for the extraction of Auditory Brainstem Responses (ABRs) from an EEG signal. It is based on adaptive filtering of signals in the wavelet domain, where the transform used is a nearly shift-invariant Complex Wavelet Transform (CWT). We compare our algorithm to two existing methods: The first simply consists of bandpass filtering the input EEG signal followed by linear averaging. The second method uses signal-adaptive filtering in the Fourier domain based on phase variance computed at each spectral component of the FFT. Realistic models of EEG and ABR are generated for this comparison. Results show that the wavelet-based method consistently outperforms the other two methods for ABR signals with an initial signal-to-noise ratio less than -20 dB.

Original languageEnglish (US)
Title of host publication2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
VolumeV
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - Jan 1 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Other

Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
CountryUnited States
CityPhiladelphia, PA
Period3/18/053/23/05

Fingerprint

Bioelectric potentials
Electroencephalography
Adaptive filtering
Fast Fourier transforms
Wavelet transforms
Signal to noise ratio

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Jacquin, A., Causevic, E., John, R., & Kovacevic, J. (2005). Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses. In 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions (Vol. V). [1416323] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2005.1416323

Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses. / Jacquin, Arnaud; Causevic, Elvir; John, Roy; Kovacevic, Jelena.

2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions. Vol. V Institute of Electrical and Electronics Engineers Inc., 2005. 1416323.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jacquin, A, Causevic, E, John, R & Kovacevic, J 2005, Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses. in 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions. vol. V, 1416323, Institute of Electrical and Electronics Engineers Inc., 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, PA, United States, 3/18/05. https://doi.org/10.1109/ICASSP.2005.1416323
Jacquin A, Causevic E, John R, Kovacevic J. Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses. In 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions. Vol. V. Institute of Electrical and Electronics Engineers Inc. 2005. 1416323 https://doi.org/10.1109/ICASSP.2005.1416323
Jacquin, Arnaud ; Causevic, Elvir ; John, Roy ; Kovacevic, Jelena. / Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses. 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions. Vol. V Institute of Electrical and Electronics Engineers Inc., 2005.
@inproceedings{f63a474facfe41879cc2cfde6f6fe68f,
title = "Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses",
abstract = "We propose a new method for the extraction of Auditory Brainstem Responses (ABRs) from an EEG signal. It is based on adaptive filtering of signals in the wavelet domain, where the transform used is a nearly shift-invariant Complex Wavelet Transform (CWT). We compare our algorithm to two existing methods: The first simply consists of bandpass filtering the input EEG signal followed by linear averaging. The second method uses signal-adaptive filtering in the Fourier domain based on phase variance computed at each spectral component of the FFT. Realistic models of EEG and ABR are generated for this comparison. Results show that the wavelet-based method consistently outperforms the other two methods for ABR signals with an initial signal-to-noise ratio less than -20 dB.",
author = "Arnaud Jacquin and Elvir Causevic and Roy John and Jelena Kovacevic",
year = "2005",
month = "1",
day = "1",
doi = "10.1109/ICASSP.2005.1416323",
language = "English (US)",
isbn = "0780388747",
volume = "V",
booktitle = "2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Adaptive complex wavelet-based filtering of EEG for extraction of evoked potential responses

AU - Jacquin, Arnaud

AU - Causevic, Elvir

AU - John, Roy

AU - Kovacevic, Jelena

PY - 2005/1/1

Y1 - 2005/1/1

N2 - We propose a new method for the extraction of Auditory Brainstem Responses (ABRs) from an EEG signal. It is based on adaptive filtering of signals in the wavelet domain, where the transform used is a nearly shift-invariant Complex Wavelet Transform (CWT). We compare our algorithm to two existing methods: The first simply consists of bandpass filtering the input EEG signal followed by linear averaging. The second method uses signal-adaptive filtering in the Fourier domain based on phase variance computed at each spectral component of the FFT. Realistic models of EEG and ABR are generated for this comparison. Results show that the wavelet-based method consistently outperforms the other two methods for ABR signals with an initial signal-to-noise ratio less than -20 dB.

AB - We propose a new method for the extraction of Auditory Brainstem Responses (ABRs) from an EEG signal. It is based on adaptive filtering of signals in the wavelet domain, where the transform used is a nearly shift-invariant Complex Wavelet Transform (CWT). We compare our algorithm to two existing methods: The first simply consists of bandpass filtering the input EEG signal followed by linear averaging. The second method uses signal-adaptive filtering in the Fourier domain based on phase variance computed at each spectral component of the FFT. Realistic models of EEG and ABR are generated for this comparison. Results show that the wavelet-based method consistently outperforms the other two methods for ABR signals with an initial signal-to-noise ratio less than -20 dB.

UR - http://www.scopus.com/inward/record.url?scp=33646818347&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646818347&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2005.1416323

DO - 10.1109/ICASSP.2005.1416323

M3 - Conference contribution

AN - SCOPUS:33646818347

SN - 0780388747

SN - 9780780388741

VL - V

BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions

PB - Institute of Electrical and Electronics Engineers Inc.

ER -