Our work concerns the analysis of the recruitment of motor units during increasing intensity stimulations and the analysis of motor unit action potential (Pa) trains during constant isotonic isometric contractions of low intensity.
Objective: to determine the variability of parameters characteristic of the motor unit, particularly its recruitment frequency and propagation velocity of its Pa.

The propagation velocity of action potentials is an interesting electromyographic parameter due to its direct relationship to the structural and functional properties of muscle. Each muscle fibre conducts ionic information along its membrane with a unique propagation velocity.

 

We have started a study concerning the estimation of muscle conduction velocity distribution (MCVD) from electrically evoked motor responses. The first aspect of this study concerns the treatment of the signal, the second concerns the exploitation of conduction velocity distribution and the third concerns the implementation of the application methods in a clinical environment. The first stage involved the evaluation of existing methods, developed for the measurement of nerve conduction velocity distribution. The adaptation of this method to muscle was carried out by using simulated signals, which has allowed the development of the MCVD estimation algorithm (Ledoux et al, 2006). The method was then applied to analyze fatigue and motor unit recruitment processes.

Modifications of the maximum motor response to repeated electrical stimulation at 20Hz. Fatigue at stimulation appears as a distribution of the motor response mainly due to decreasing muscle conduction velocities along the fibres. This is shown by the MCVD calculated due to the optimized method.

The fine analysis of Pa in contraction caused by electrical stimulation or during voluntary contractions is carried out in collaboration with professors Dimitrov and Dimitrova of the Academy of Science of Bulgaria. Surface EMG measurements were performed thanks to monopolar multi-electrode devices during various muscular solicitations leading to fatigue. The preliminary results confirm previously published data: decreasing muscle conduction velocities translate into a distribution of the potential with time, as well as a reduction in its amplitude. These analyses led to the development of a new muscle fatigue follow-up index using sensitive spectral indices (Dimitrova et al, 2005, 2006, 2007).