Paper
Tutorial on MUedit: An open-source software for identifying and analysing the discharge timing of motor units from electromyographic signals
Published Jul 17, 2023 · S. Avrillon, François Hug, Ciara Gibbs
bioRxiv
15
Citations
2
Influential Citations
Abstract
We introduce the open-source software MUedit and we describe its use for identifying the discharge timing of motor units from all types of electromyographic (EMG) signals recorded with multi-channel systems. MUedit performs EMG decomposition using a blind-source separation approach. Following this, users can display the estimated motor unit pulse trains and inspect the accuracy of the automatic detection of discharge times. When necessary, users can correct the automatic detection of discharge times and recalculate the motor unit pulse train with an updated separation vector. Here, we provide an open-source software and a tutorial that guides the user through i) the parameters and steps of the decomposition algorithm, and ii) the manual editing of motor unit pulse trains. Further, we provide simulated and experimental EMG signals recorded with grids of surface electrodes and intramuscular electrode arrays to benchmark the performance of MUedit. Finally, we discuss advantages and limitations of the blind-source separation approach for the study of motor unit behaviour during muscle contractions in humans.
MUedit is an open-source software that accurately identifies motor unit discharge timing from electromyographic signals, allowing users to analyze muscle contractions in humans.
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