emgGO

版本 2.0 (4.7 MB) 作者: GallVp
A toolbox for offline muscle activity onset/offset detection in multi-channel EMG data.
0.0
(0)
60.0 次下载
更新时间 2022/3/20
在 GitHub 上查看许可证

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.

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
兼容任何版本
平台兼容性
Windows macOS Linux
标签 添加标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Helpers

Plotters

algorithms/extendedDTA

libs/PSOt

libs/PSOt/hiddenutils

libs/PSOt/nnet

libs/PSOt/testfunctions

libs/energyop

optimisation

版本 已发布 发行说明
2.0

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。
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。