emgGO

A toolbox for offline muscle activity onset/offset detection in multi-channel EMG data.

https://github.com/GallVp/emgGO

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emgGO

emgGO (electromyography, graphics and optimisation) is a toolbox for offline muscle activity onset/offset detection in multi-channel EMG data.

emgGO GUIsvisualEEG main window


Fig 1. The GUI tools of emgGo which allow interactive processing of data.

Related Publications

  1. Optimal Automatic Detection of Muscle Activation Intervals, Journal of Electromyography and Kinesiology, doi: 10.1016/j.jelekin.2019.06.010

Compatibility

Currently emgGO is being developed on macOS Mojave, MATLAB 2017b.

Installation

  1. Clone the git repository using git. Or, download a compressed copy here.
$ git clone https://github.com/GallVp/emgGO
  1. From MATLAB file explorer, enter the emgGO folder by double clicking it. Follow the tutorials to experiment with the sample data.

Tutorials

Third Party Libraries

emgGO uses following third party libraries. The licenses for these libraries can be found next to source files in their respective libs/thirdpartlib folders.

  1. energyop Copyright (c) 2014, Hooman Sedghamiz. Source is available here.
  2. PSOt Copyright (c) 2005, Brian Birge. Source is available here.

Cite As

GallVp (2026). emgGO (https://github.com/GallVp/emgGO/releases/tag/v2.0), GitHub. Retrieved .

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General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
2.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.