MUedit is a Matlab app that decomposes electromyographic (EMG) signals recorded from multiple electrodes into individual motor unit pulse trains using fast independent component analysis (fastICA). You can easily adjust the parameters of the algorithm to the specificity of your experimental settings. After the decomposition, you can display and edit the output of the fastICA, i.e., the motor unit pulse trains.

We provide a step-by-step protocol (User_manual.pdf) to facilitate the implementation of MUedit in any experimental settings. You can also read our preprint that describes the method, the main steps of the experiments, and the capability boundaries of the app (https://www.biorxiv.org/content/10.1101/2023.07.13.548568v1).

You can download the data presented in the paper at https://figshare.com/projects/Data_for_MUedit/172314

A version of the decomposition algorithm coded with Python (Python 3.9.15) by Ciara Gibbs ([email protected]) will be available soon at https://github.com/ciaragibbs/MUEdit_Python

For technical assistance and support, please contact: Dr. Simon Avrillon / Sir Michael Uren Hub / Imperial College London / 86 Wood Ln / London W12 0BZ / E-mail address: [email protected]

If you use MUedit in your experimental setting, please cite the following preprint.

Avrillon S, Hug F, Gibbs C & Farina D. (2023). Tutorial on MUedit: An open-source software for identifying and analysing the discharge timing of motor units from electromyographic signals. bioRxiv, 2023.2007.2013.548568.