lspieser
commented
7 months ago Hi @brainhackorg/project-monitors my project is ready!
Open lspieser opened 7 months ago
lspieser
commented
7 months ago Hi @brainhackorg/project-monitors my project is ready!
arnaudletroter
commented
7 months ago Thank you for submitting your project to BrainHack Marseille 2023. Your project is now visible online !
Arnaud for the BHM organization team.
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
Good first issues
Communication channels
https://mattermost.brainhack.org/brainhack/channels/bhg23-marseille-myonset
Skills
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.
Hi @brainhackorg/project-monitors my project is ready!