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

M. J. Stam; B. C. M. van Wijk; P. Sharma; M. Beudel; D. A. Piña-Fuentes; R. M. A. de Bie; P. R. Schuurman; W. J. Neumann; A. W. G. Buijink

doi:https://doi.org/10.1016/j.clinph.2022.11.011

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

M. J. Stam, B. C. M. van Wijk, P. Sharma, M. Beudel, D. A. Piña-Fuentes, R. M. A. de Bie, P. R. Schuurman, W. J. Neumann, A. W. G. Buijink

Research output: Contribution to journal › Article › Academic › peer-review

4 Citations (Scopus)

Abstract

Objective: 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. Methods: 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 PerceptTM PC system in nine Parkinson's disease patients with stimulation OFF (“OFF-DBS”; anode disconnected) and ON at 0 mA (“ON-DBS 0 mA”; anode connected). Findings were verified with simulated ECG-contaminated time series. Results: 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. Conclusions: The SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings are adequately chosen. Significance: ECG suppression methods enable analysis of disease-specific neural activity from signals affected by ECG artifacts.

Original language	English
Pages (from-to)	147-161
Number of pages	15
Journal	Clinical neurophysiology
Volume	146
Early online date	2 Dec 2022
DOIs	https://doi.org/10.1016/j.clinph.2022.11.011
Publication status	Published - Feb 2023

Keywords

Artifacts
Beta
ECG
Local field potentials
Parkinson's disease

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https://doi.org/10.1016/j.clinph.2022.11.011

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@article{0f94d7e58c9849f8b44c4f03b4030244,

title = "A comparison of methods to suppress electrocardiographic artifacts in local field potential recordings",

abstract = "Objective: 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. Methods: 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 PerceptTM PC system in nine Parkinson's disease patients with stimulation OFF (“OFF-DBS”; anode disconnected) and ON at 0 mA (“ON-DBS 0 mA”; anode connected). Findings were verified with simulated ECG-contaminated time series. Results: 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. Conclusions: The SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings are adequately chosen. Significance: ECG suppression methods enable analysis of disease-specific neural activity from signals affected by ECG artifacts.",

keywords = "Artifacts, Beta, ECG, Local field potentials, Parkinson's disease",

author = "Stam, {M. J.} and {van Wijk}, {B. C. M.} and P. Sharma and M. Beudel and Pi{\~n}a-Fuentes, {D. A.} and {de Bie}, {R. M. A.} and Schuurman, {P. R.} and Neumann, {W. J.} and Buijink, {A. W. G.}",

note = "Funding Information: MJS was funded by the Amsterdam UMC TKI-PPP grant (2021 call). BCMvW received funding from an EU Joint Programme – Neurodegenerative Disease Research (JPND) project. The project is supported through the following funding organisations under the aegis of JPND – www.jpnd.eu: the Netherlands Organisation for Health Research and Development (ZonMw) – The Netherlands. RMAdB reported grants from Stichting AMC Foundation, Netherlands Organization for Health Research and Development, Stichting Parkinson Nederland, Medtronic, and Neuroderm, all paid to institution and outside the submitted work. WJN was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 424778381 – TRR 295. AWGB was supported by travel stipends from the Dr. Jan Meerwaldtstichting and the Remmert Adriaan Laan fonds. The authors thank all patients for their participation in this study. Publisher Copyright: {\textcopyright} 2022 International Federation of Clinical Neurophysiology",

year = "2023",

month = feb,

doi = "https://doi.org/10.1016/j.clinph.2022.11.011",

language = "English",

volume = "146",

pages = "147--161",

journal = "Clinical neurophysiology",

issn = "1388-2457",

publisher = "Elsevier Ireland Ltd",

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TY - JOUR

T1 - A comparison of methods to suppress electrocardiographic artifacts in local field potential recordings

AU - Stam, M. J.

AU - van Wijk, B. C. M.

AU - Sharma, P.

AU - Beudel, M.

AU - Piña-Fuentes, D. A.

AU - de Bie, R. M. A.

AU - Schuurman, P. R.

AU - Neumann, W. J.

AU - Buijink, A. W. G.

N1 - Funding Information: MJS was funded by the Amsterdam UMC TKI-PPP grant (2021 call). BCMvW received funding from an EU Joint Programme – Neurodegenerative Disease Research (JPND) project. The project is supported through the following funding organisations under the aegis of JPND – www.jpnd.eu: the Netherlands Organisation for Health Research and Development (ZonMw) – The Netherlands. RMAdB reported grants from Stichting AMC Foundation, Netherlands Organization for Health Research and Development, Stichting Parkinson Nederland, Medtronic, and Neuroderm, all paid to institution and outside the submitted work. WJN was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 424778381 – TRR 295. AWGB was supported by travel stipends from the Dr. Jan Meerwaldtstichting and the Remmert Adriaan Laan fonds. The authors thank all patients for their participation in this study. Publisher Copyright: © 2022 International Federation of Clinical Neurophysiology

PY - 2023/2

Y1 - 2023/2

N2 - Objective: 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. Methods: 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 PerceptTM PC system in nine Parkinson's disease patients with stimulation OFF (“OFF-DBS”; anode disconnected) and ON at 0 mA (“ON-DBS 0 mA”; anode connected). Findings were verified with simulated ECG-contaminated time series. Results: 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. Conclusions: The SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings are adequately chosen. Significance: ECG suppression methods enable analysis of disease-specific neural activity from signals affected by ECG artifacts.

AB - Objective: 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. Methods: 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 PerceptTM PC system in nine Parkinson's disease patients with stimulation OFF (“OFF-DBS”; anode disconnected) and ON at 0 mA (“ON-DBS 0 mA”; anode connected). Findings were verified with simulated ECG-contaminated time series. Results: 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. Conclusions: The SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings are adequately chosen. Significance: ECG suppression methods enable analysis of disease-specific neural activity from signals affected by ECG artifacts.

KW - Artifacts

KW - Beta

KW - ECG

KW - Local field potentials

KW - Parkinson's disease

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DO - https://doi.org/10.1016/j.clinph.2022.11.011

M3 - Article

C2 - 36543611

SN - 1388-2457

VL - 146

SP - 147

EP - 161

JO - Clinical neurophysiology

JF - Clinical neurophysiology

ER -

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

Abstract

Keywords

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