Adapted filter banks for feature extraction in transcranial magnetic stimulation evoked responses.
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...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 49; no. 2; pp. 221 - 232 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2011
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104569961&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104569961 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2011 vid: 49 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104569961 NLM21222168 2010935212 10.1007/s11517-010-0726-7 NLM21222168 104569961 ppf: 221 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Adapted filter banks for feature extraction in transcranial magnetic stimulation evoked responses. aug: au: Harris AR Schwerdtfeger K Strauss DJ Harris, Arief R Schwerdtfeger, Karsten Strauss, Daniel J affil: Computational Diagnostics and Biocybernetics Unit, Saarland University Hospital and Saarland University of Applied Sciences, Homburg/Saar, Germany sug: subj: Brain Physiology Evoked Potentials Physiology Diagnosis, Neurologic Methods Adult Algorithms Electroencephalography Methods Female Male Signal Processing, Computer Assisted Young Adult Adult: 19-44 years Female Male ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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