A comparison of methods to suppress electrocardiographic artifacts in local field potential recordings.


Journal

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
ISSN: 1872-8952
Titre abrégé: Clin Neurophysiol
Pays: Netherlands
ID NLM: 100883319

Informations de publication

Date de publication:
02 2023
Historique:
received: 14 07 2022
revised: 06 10 2022
accepted: 15 11 2022
pubmed: 22 12 2022
medline: 25 1 2023
entrez: 21 12 2022
Statut: ppublish

Résumé

Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are often contaminated with electrocardiographic (ECG) artifacts that hinder the detection of disease-specific electrical brain activity. Three ECG suppression methods were evaluated: (1) QRS interpolation of the Perceive toolbox, (2) template subtraction, and (3) singular value decomposition (SVD). LFPs were recorded with the Medtronic Percept ECG artifacts were present in 10 out of 18 ON-DBS 0 mA recordings. All ECG suppression methods drastically reduced artifact-induced beta band (13-35 Hz) power and at least partly recovered the beta peak and beta burst dynamics. Using external ECG recordings and lengthening artifact epoch length improved the performance of the suppression methods. Increasing epoch length, however, elevated the risk of flattening the beta peak and losing beta burst dynamics. The SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings are adequately chosen. ECG suppression methods enable analysis of disease-specific neural activity from signals affected by ECG artifacts.

Identifiants

pubmed: 36543611
pii: S1388-2457(22)00948-8
doi: 10.1016/j.clinph.2022.11.011
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

147-161

Informations de copyright

Copyright © 2022 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Auteurs

M J Stam (MJ)

Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands.

B C M van Wijk (BCM)

Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands; Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

P Sharma (P)

Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Department of Electrical Engineering and Information Technology, Otto von Guericke University, Magdeburg, Germany.

M Beudel (M)

Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands.

D A Piña-Fuentes (DA)

Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands.

R M A de Bie (RMA)

Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands.

P R Schuurman (PR)

Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands.

W-J Neumann (WJ)

Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.

A W G Buijink (AWG)

Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands. Electronic address: a.w.buijink@amsterdamumc.nl.

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Classifications MeSH