emgGO
A toolbox for offline muscle activity onset/offset detection in multi-channel EMG data.
emgGO
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.
Related Publications
- 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
- 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.
Tutorials
- 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
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.
引用格式
GallVp (2024). emgGO (https://github.com/GallVp/emgGO/releases/tag/v2.0), GitHub. 检索来源 .
MATLAB 版本兼容性
创建方式
R2017b
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平台兼容性
Windows macOS Linux标签
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版本 | 已发布 | 发行说明 | |
---|---|---|---|
2.0 |
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要查看或报告此来自 GitHub 的附加功能中的问题,请访问其 GitHub 仓库。