MYOnset: a Python package to detect EMG onset for electrophysiological studies

[lspieser]

Title

MYOnset: a Python package to detect EMG onset for electrophysiological studies

Leaders

Laure Spieser and Boris Burle
Laboratoire de Neurosciences Cognitives, Aix-Marseille University, CNRS

Collaborators

No response

Brainhack Global 2023 Event

Brainhack Marseille

Project Description

Among brain’s functions, selecting and executing actions is certainly one of the most important. In this research domain, investigating electromyographic (EMG) activity of muscles involved in actions execution can be an easy way to collect more information on processes of interest. Yet, once EMG is recorded, one needs to process and analyse EMG data in addition to other collected data (e.g., behavior, electrophysiological recordings, etc). Particularly, the detection of EMG bursts onsets is often a critical processing step. However, few tools are available to achieve it, and none was really suitable to use in typical experimental designs of experimental psychology such as reaction time tasks. To meet this need, we developed MYOnset, a Python package designed to help such EMG recordings processing, with particular attention given to the step of EMG bursts onsets and offsets detection.
MYOnset integrates tools for standard preprocessing of EMG recordings, like bipolar derivation and filtering. Regarding EMG onset detection, MYOnset proposes a two-steps method: first, an automatic detection of EMG bursts onsets and offsets, second, a step of visualization and manual correction of detected onsets and offsets. MYOnset integrates two algorithms combining different automatic detection methods. Further, MYOnset proposes a specific window for the visualization and manual correction step, which the most time-consuming step and for which no tool was available. This window offers an adapted view for EMG signals and the associated markers, i.e., experimental triggers and EMG onsets and offsets automatically detected. Importantly, user can interact with onset and offset markers to adjust onsets/offsets positions, insert new onsets/offsets, and remove existing onsets/offsets.
MYOnset package is available on PyPI (https://pypi.org/project/myonset/) and GitHub (https://github.com/lspieser/myonset).

Link to project repository/sources

https://github.com/lspieser/myonset

Goals for Brainhack Global

• discuss package organisation
• implement new detection methods (e.g., bayesian changepoint detection)
• add code testing

Good first issues

1. issue one:
   none yet...
2. issue two:

Communication channels

https://mattermost.brainhack.org/brainhack/channels/bhg23-marseille-myonset

Skills

• python coding : 80%
• share ideas : 70%
• electrophysiology : 10%

Onboarding documentation

No response

What will participants learn?

Just have fun together ! and learn on electromyography signal if you're interested

Data to use

No response

Number of collaborators

1

Credit to collaborators

Project contributors are listed on the project README

Image

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Type

coding_methods

Development status

2_releases_existing

Topic

data_visualisation, physiology

Tools

other

Programming language

Python

Modalities

other

Git skills

0_no_git_skills

Anything else?

No response

Things to do after the project is submitted and ready to review.

• Add a comment below the main post of your issue saying: Hi @brainhackorg/project-monitors my project is ready!
• Twitter-sized summary of your project pitch.

[lspieser]

Hi @brainhackorg/project-monitors my project is ready!

[arnaudletroter]

Thank you for submitting your project to BrainHack Marseille 2023.
Your project is now visible online !

Arnaud for the BHM organization team.