A novel method for electrophysiological analysis of EMG signals using MesaClip

Lukasz Wiklendt; Simon J.H. Brookes; Marcello Costa; Lee Travis; Nick J. Spencer; Phil G. Dinning

doi:10.3389/fphys.2020.00484

A novel method for electrophysiological analysis of EMG signals using MesaClip

Lukasz Wiklendt, Simon J.H. Brookes, Marcello Costa, Lee Travis, Nick J. Spencer, Phil G. Dinning

College of Medicine and Public Health

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

9 Citations (Scopus)

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Abstract

In electrophysiology, many methods have been proposed for the analysis of action potential firing frequencies. The aim of this study was to present an algorithm developed for a continuous wavelet transform that enables the filtering out of frequencies contributing to the shapes of action potentials (spikes), whilst retaining the frequencies that encode the periodicity of spike trains. The continuous wavelet transform allows us to decompose a signal into its constituent frequencies. A signal with a single event, such as a spike, is composed of frequencies that characterize the shape of the spike. A signal with two spikes will also be composed of frequencies characterizing the shape of the action potential, but in addition will include a substantial portion of its power at the frequency corresponding to the time-difference between the two spikes. This is achieved by clipping peaks from the wavelet amplitudes that are narrower than a given minimum number of phase cycles. We present some application examples in both synthetic signals and electrophysiological recordings. This new approach can provide a major new analytical tool for analysis of electrophysiological signals.

Original language	English
Article number	484
Number of pages	10
Journal	Frontiers in Physiology
Volume	11
DOIs	https://doi.org/10.3389/fphys.2020.00484
Publication status	Published - Jun 2020

Bibliographical note

Copyright © 2020 Wiklendt, Brookes, Costa, Travis, Spencer and Dinning. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Keywords

Action potential
Artifact removal
Non-harmonic model
Time-frequency analysis
Wavelet transform

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10.3389/fphys.2020.00484Licence: CC BY

Published versionFinal published version, 8.43 MBLicence: CC BY

Cite this

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title = "A novel method for electrophysiological analysis of EMG signals using MesaClip",

abstract = "In electrophysiology, many methods have been proposed for the analysis of action potential firing frequencies. The aim of this study was to present an algorithm developed for a continuous wavelet transform that enables the filtering out of frequencies contributing to the shapes of action potentials (spikes), whilst retaining the frequencies that encode the periodicity of spike trains. The continuous wavelet transform allows us to decompose a signal into its constituent frequencies. A signal with a single event, such as a spike, is composed of frequencies that characterize the shape of the spike. A signal with two spikes will also be composed of frequencies characterizing the shape of the action potential, but in addition will include a substantial portion of its power at the frequency corresponding to the time-difference between the two spikes. This is achieved by clipping peaks from the wavelet amplitudes that are narrower than a given minimum number of phase cycles. We present some application examples in both synthetic signals and electrophysiological recordings. This new approach can provide a major new analytical tool for analysis of electrophysiological signals.",

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AU - Wiklendt, Lukasz

AU - Brookes, Simon J.H.

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AU - Travis, Lee

AU - Spencer, Nick J.

AU - Dinning, Phil G.

N1 - Copyright © 2020 Wiklendt, Brookes, Costa, Travis, Spencer and Dinning. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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N2 - In electrophysiology, many methods have been proposed for the analysis of action potential firing frequencies. The aim of this study was to present an algorithm developed for a continuous wavelet transform that enables the filtering out of frequencies contributing to the shapes of action potentials (spikes), whilst retaining the frequencies that encode the periodicity of spike trains. The continuous wavelet transform allows us to decompose a signal into its constituent frequencies. A signal with a single event, such as a spike, is composed of frequencies that characterize the shape of the spike. A signal with two spikes will also be composed of frequencies characterizing the shape of the action potential, but in addition will include a substantial portion of its power at the frequency corresponding to the time-difference between the two spikes. This is achieved by clipping peaks from the wavelet amplitudes that are narrower than a given minimum number of phase cycles. We present some application examples in both synthetic signals and electrophysiological recordings. This new approach can provide a major new analytical tool for analysis of electrophysiological signals.

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A novel method for electrophysiological analysis of EMG signals using MesaClip

Abstract

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Keywords

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