Neurophysiological Factors Affecting Muscle Innervation Zone Estimation Using Surface EMG: A Simulation Study

Overview

Journal Biosensors (Basel)

Specialty Biotechnology

Date 2021 Oct 22

PMID 34677312

Citations 1

Authors

Chengjun Huang

Maoqi Chen

Xiaoyan Li

Yingchun Zhang

Sheng Li

Ping Zhou

Affiliations

Soon will be listed here.

Abstract

Surface electromyography (EMG) recorded by a linear or 2-dimensional electrode array can be used to estimate the location of muscle innervation zones (IZ). There are various neurophysiological factors that may influence surface EMG and thus potentially compromise muscle IZ estimation. The objective of this study was to evaluate how surface-EMG-based IZ estimation might be affected by different factors, including varying degrees of motor unit (MU) synchronization in the case of single or double IZs. The study was performed by implementing a model simulating surface EMG activity. Three different MU synchronization conditions were simulated, namely no synchronization, medium level synchronization, and complete synchronization analog to M wave. Surface EMG signals recorded by a 2-dimensional electrode array were simulated from a muscle with single and double IZs, respectively. For each situation, the IZ was estimated from surface EMG and compared with the one used in the model for performance evaluation. For the muscle with only one IZ, the estimated IZ location from surface EMG was consistent with the one used in the model for all the three MU synchronization conditions. For the muscle with double IZs, at least one IZ was appropriately estimated from interference surface EMG when there was no MU synchronization. However, the estimated IZ was different from either of the two IZ locations used in the model for the other two MU synchronization conditions. For muscles with a single IZ, MU synchronization has little effect on IZ estimation from electrode array surface EMG. However, caution is required for multiple IZ muscles since MU synchronization might lead to false IZ estimation.

Citing Articles

Muscle innervation zone estimation from monopolar high-density M-waves using principal component analysis and radon transform.

Huang C, Lu Z, Chen M, Klein C, Zhang Y, Li S Front Physiol. 2023; 14:1137146.

PMID: 37008017 PMC: 10050562. DOI: 10.3389/fphys.2023.1137146.

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