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Medical & Biological Engineering & Computing

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01-02-2011 | Original Article

Adapted filter banks for feature extraction in transcranial magnetic stimulation evoked responses

Authors: Arief R. Harris, Karsten Schwerdtfeger, Daniel J. Strauss

Published in: Medical & Biological Engineering & Computing | Issue 2/2011

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Abstract

A novel adaptive and approximate shift-invariant wavelet packet feature extraction scheme for event-related potentials (ERPs) in the electroencephalogram (EEG) is introduced in this paper. In this algorithm, the shift-invariant wavelet packed decomposition is done by integrating a cost function for decimation decision in each sub-band expansion. Additionally, a shape adaptation of the wavelet is implemented to find the best adapted wavelet shape for a given class of ERPs. This scheme is used to analyze the time course of the impact of single-pulse transcranial magnetic stimulation (TMS) to the auditory ERPs. We show that the proposed scheme is able to extract even slightest impacts of TMS, making it a promising tool for the extraction of weak ERPs components, particularly in hybrid TMS–EEG/ERP setups.

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Title: Adapted filter banks for feature extraction in transcranial magnetic stimulation evoked responses
Authors: Arief R. Harris
Karsten Schwerdtfeger
Daniel J. Strauss
Publication date: 01-02-2011
Publisher: Springer-Verlag
Published in: Medical & Biological Engineering & Computing / Issue 2/2011
Print ISSN: 0140-0118
Electronic ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-010-0726-7

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