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Low back muscle action potential conduction velocity estimated using high-density electromyography.

Niels P Brouwer¹, Ali Tabasi¹, Idsart Kingma¹

¹Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands.

Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology

|July 20, 2022

Summary

This summary is machine-generated.

Estimating low back muscle conduction velocity (CV) using high-density surface electromyography offers a reliable method for monitoring muscle fatigue. This technique provides better insights than spectral analysis alone.

Keywords:

Erector spinae HDEMG Muscle fiber conduction velocity Propagation velocity Trunk extensor muscles

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Area of Science:

Biomechanics
Neuroscience
Sports Medicine

Background:

Surface electromyography (sEMG) spectral content changes indicate low back muscle fatigue.
However, the reliability of these spectral changes is questionable.
Motor unit action potential conduction velocity (CV) is a more direct fatigue indicator.

Purpose of the Study:

To estimate low back muscle CV using high-density multi-channel EMG.
To evaluate peak-delay and cross-correlation methods for CV estimation.
To assess the feasibility of CV estimation for low back muscle fatigue monitoring.

Main Methods:

High-density multi-channel EMG was recorded from 14 healthy males during a fatiguing lumbar flexion task.
Peak-delay and cross-correlation techniques were employed to estimate CV.
Data analysis focused on identifying propagating potentials and calculating CV values.

Main Results:

Feasible CV estimates were obtained for 10 participants (118/560 sites), primarily over the iliocostalis lumborum.
The two methods yielded comparable CV estimates, indicating good agreement.
A subset of sites near the spine showed systematically overestimated CV values.

Conclusions:

Estimating low back muscle CV is feasible with high-density EMG and specific signal processing methods.
This approach may enhance the understanding and monitoring of low back muscle fatigue.
Further refinement is needed to address overestimation issues near the spine.