Med Biol Eng Comput - Adapted filter banks for feature extraction in transcranial magnetic stimulation evoked responses.

Tópicos

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Resumo

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.

Resumo Limpo

novel adapt approxim shiftinvari wavelet packet featur extract scheme eventrel potenti erp electroencephalogram eeg introduc paper algorithm shiftinvari wavelet pack decomposit done integr cost function decim decis subband expans addit shape adapt wavelet implement find best adapt wavelet shape given class erp scheme use analyz time cours impact singlepuls transcrani magnet stimul tms auditori erp show propos scheme abl extract even slightest impact tms make promis tool extract weak erp compon particular hybrid tmseegerp setup

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