Motor unit identification in the M waves recorded by high-density electromyogram
Objective: We describe and test the methodology supporting the identification of individual motor unit (MU) firings in the motor response (M wave) to percutaneous nerve stimulation recorded by surface high-density electromyography (HD-EMG) on synthetic and experimental data. Methods: A set of simulated voluntary contractions followed by 100 simulated M waves with a normal distribution (MU mean firing latency: 10 ms, Standard Deviation - SDLAT 0.1-1.3 ms) constituted the synthetic signals. In experimental condition, at least 52 progressively increasing M waves were elicited in the soleus muscle of 12 males, at rest (REST), and at 10% (C10) and 20% (C20) of maximal voluntary contraction (MVC). The MU decomposition filters were identified from 15-20 s long isometric plantar flexions performed at 10-70% of MVC and, afterwards, applied to M waves. Results: Synthetic signal analysis demonstrated high accuracy of MU identification in M waves (precision ≥ 85%). In experimental conditions 42.6 ± 11.2 MUs per participant were identified from voluntary contractions. When the MU filters were applied to the M wave recordings, 28.4 ± 14.3, 23.7 ± 14.9 and 20.2 ± 13.5 MU firings were identified in the maximal M waves, with individual MU firing latencies of 10.0 ± 2.8 ( SDLAT : 1.2 ± 1.2), 9.6 ± 3.0 ( SDLAT : 1.5 ± 1.3) and 10.1 ± 3.7 ( SDLAT : 1.7 ± 1.6) ms in REST, C10 and C20 conditions, respectively. Conclusion and significance: We present evidence that supports the feasibility of identifying MU firings in M waves recorded by HD-EMG.
Funding
Slovenian Research Agency (Grant Number: P2-0041)
History
School
- Sport, Exercise and Health Sciences
Published in
IEEE Transactions on Biomedical EngineeringVolume
70Issue
5Pages
1662 - 1672Publisher
Institute of Electrical and Electronics EngineersVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher statement
This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2022-11-22Publication date
2022-11-28Copyright date
2022ISSN
0018-9294eISSN
1558-2531Publisher version
Language
- en