emgGO (electromyography, graphics and optimisation) is a toolbox for offline muscle activity onset/offset detection in multi-channel EMG data.
Fig 1. The GUI tools of emgGo which allow interactive processing of data.
- Optimal Automatic Detection of Muscle Activation Intervals, Journal of Electromyography and Kinesiology, doi: 10.1016/j.jelekin.2019.06.010
Currently emgGO is being developed on macOS Mojave, MATLAB 2017b.
- Clone the git repository using git. Or, download a compressed copy here.
$ git clone https://github.com/GallVp/emgGO
- From MATLAB file explorer, enter the emgGO folder by double clicking it. Follow the tutorials to experiment with the sample data.
- emgGO: An Overview
- How to Import Data in emgGO?
- How to Detect Onsets/Offsets?
- How to Create a Processing Pipeline?
- The Extended Double Thresholding Algorithm
emgGO uses following third party libraries. The licenses for these libraries can be found next to source files in their respective libs/thirdpartlib folders.