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.

https://jingweitoo.wordpress.com/

4.4

(8)

4K Downloads

Updated 11 Dec 2020

View License on GitHub

Jx-EMGT : Electromyography (EMG) Feature Extraction Toolbox

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* 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

Windows macOS Linux

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Acknowledgements

Inspired: Identify Arm Motions Using EMG Signals and Deep Learning.

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Version	Published	Release Notes
1.4	11 Dec 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox/releases/tag/1.4	Download

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

MLA	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.
APA	Too, J., Rahim, A., & Mohd, N. (2019). Classification of Hand Movements based on Discrete Wavelet Transform and Enhanced Feature Extraction. International Journal of Advanced Computer Science and Applications, 10(6). The Science and Information Organization. Retrieved from https://doi.org/10.14569%2Fijacsa.2019.0100612
BibTeX	@article{Too_2019, doi = {10.14569/ijacsa.2019.0100612}, url = {https://doi.org/10.14569%2Fijacsa.2019.0100612}, year = 2019, publisher = {The Science and Information Organization}, volume = {10}, number = {6}, author = {Jingwei Too and Abdul Rahim and Norhashimah Mohd}, title = {Classification of Hand Movements based on Discrete Wavelet Transform and Enhanced Feature Extraction}, journal = {International Journal of Advanced Computer Science and Applications} }

MLA	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.
APA	Too, J., Abdullah, A., Saad, N. M., & Tee, W. (2019). EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization. Computation, 7(1), 12. MDPI AG. Retrieved from https://doi.org/10.3390%2Fcomputation7010012
BibTeX	@article{Too_2019, doi = {10.3390/computation7010012}, url = {https://doi.org/10.3390%2Fcomputation7010012}, year = 2019, month = {feb}, publisher = {{MDPI} {AG}}, volume = {7}, number = {1}, pages = {12}, author = {Jingwei Too and Abdul Abdullah and Norhashimah Mohd Saad and Weihown Tee}, title = {{EMG} Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization}, journal = {Computation} }