Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
<jats:title>Abstract</jats:title>
<jats:sec>
<jats:title>Objective</jats:title>
<jats:p>High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Approach</jats:title>
<jats:p>
We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous fat thickness), maximum anatomical cross-sectional area (ACSA
<jats:sub>max</jats:sub>
), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound, magnetic resonance imaging, and muscle biopsy of the biceps brachii muscle from two groups of participants – untrained-controls (UT=14) and strength-trained (>3 years of training, ST=16) – while they performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.
</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Main results</jats:title>
<jats:p>
ST subjects showed lower MED (UT: 4.8 ± 1.4 vs. ST: 3.7 ± 0.8 mm) associated to a greater number of identified motor units (UT: 21.3 ± 10.2 vs. ST: 29.2 ± 11.8 MUs/subject). Both groups showed a negative correlation between MED and the number of identified MUs at low forces (r= −0.6, p=0.002 at 15% MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSA
<jats:sub>max</jats:sub>
(r=0.48, p=0.03) at 15% MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces.
</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Significance</jats:title>
<jats:p>
Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSA
<jats:sub>max</jats:sub>
are also relevant parameters of influence for current decomposition algorithms.
</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Objective</jats:title>
<jats:p>High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Approach</jats:title>
<jats:p>
We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous fat thickness), maximum anatomical cross-sectional area (ACSA
<jats:sub>max</jats:sub>
), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound, magnetic resonance imaging, and muscle biopsy of the biceps brachii muscle from two groups of participants – untrained-controls (UT=14) and strength-trained (>3 years of training, ST=16) – while they performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.
</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Main results</jats:title>
<jats:p>
ST subjects showed lower MED (UT: 4.8 ± 1.4 vs. ST: 3.7 ± 0.8 mm) associated to a greater number of identified motor units (UT: 21.3 ± 10.2 vs. ST: 29.2 ± 11.8 MUs/subject). Both groups showed a negative correlation between MED and the number of identified MUs at low forces (r= −0.6, p=0.002 at 15% MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSA
<jats:sub>max</jats:sub>
(r=0.48, p=0.03) at 15% MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces.
</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Significance</jats:title>
<jats:p>
Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSA
<jats:sub>max</jats:sub>
are also relevant parameters of influence for current decomposition algorithms.
</jats:p>
</jats:sec>
Date Issued
2022-02-08
Date Acceptance
2022-02-08
Citation
2022
Copyright Statement
Copyright © 2022 IOP Publishing Ltd. This is an author-created, un-copyedited version of an article accepted for publication/published in Journal of Neural Engineering. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/1741-2552/ac823d.
Publication Status
Published