EMG Feature Extraction Toolbox

Version 1.4 (17.4 KB) by Jingwei Too
This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.
Updated 11 Dec 2020

Jx-EMGT : Electromyography (EMG) Feature Extraction Toolbox


* This toolbox offers 40 types of EMG features

* The < A_Main.m file > demos how the feature extraction methods can be applied using generated sample signal.

* The detailed of this Jx-EMGT toolbox can be found at https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox

Cite As

Too, Jingwei, et al. “Classification of Hand Movements Based on Discrete Wavelet Transform and Enhanced Feature Extraction.” International Journal of Advanced Computer Science and Applications, vol. 10, no. 6, The Science and Information Organization, 2019, doi:10.14569/ijacsa.2019.0100612.

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Too, Jingwei, et al. “EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization.” Computation, vol. 7, no. 1, MDPI AG, Feb. 2019, p. 12, doi:10.3390/computation7010012.

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MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
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Version Published Release Notes

See release notes for this release on GitHub: https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox/releases/tag/1.4

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.