MUAP number estimates in surface EMG: template-matching methods and their performance boundaries

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Surface electromyogram (EMG) quantification methods currently lack accuracy in reflecting neural commands to muscles.
• Motor unit action potentials (MUAPs) in EMG signals contain valuable information about motor unit recruitment and firing rates.

Purpose of the Study:

• To estimate the number of MUAPs in surface EMG signals using template-matching techniques.
• To investigate the impact of MUAP superposition and duration on estimation accuracy.
• To compare MUAP characteristics recorded by a ring electrode versus a standard differential electrode.

Main Methods:

• Representing surface MUAP shapes with a limited set of waveforms.
• Employing template-matching algorithms to identify MUAP occurrences in simulated and experimental EMG signals.
• Comparing recordings from a selective multiple concentric ring electrode with a standard differential EMG electrode.

Main Results:

• Simulation studies showed MUAP superposition and duration constrain template-matching accuracy for MUAP number estimation.
• Experimental data indicated that ring surface electrodes minimally reduce MUAP duration.
• Reduced pickup area of the ring electrode primarily decreased MUAP superposition, improving estimation.
• Accurate MUAP number estimation from surface EMG is limited by MUAP duration, even with selective electrodes.

Conclusions:

• Template-matching techniques can estimate MUAP numbers in surface EMG signals, providing a more accurate reflection of neural drive.
• MUAP duration is a critical factor limiting the accuracy of MUAP number estimation from surface EMG.
• Selective electrodes, by reducing pickup area, can decrease MUAP superposition but do not significantly alter MUAP duration.