EMG Feature Extraction Toolbox

Version 1.4 (17,4 KB) von 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/

Verfolgen

4.4

(8)

4,3K Downloads

Aktualisiert 11. Dez 2020

Lizenz auf GitHub anzeigen

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

Zitieren als

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.

Mehrere Stile anzeigen

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.

Mehrere Stile anzeigen

Kompatibilität der MATLAB-Version

Erstellt mit R2018a

Kompatibel mit allen Versionen

Plattform-Kompatibilität

Windows macOS Linux

Tags Tags hinzufügen

Quellenangaben

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

Community Treasure Hunt

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

Start Hunting!

Version	Veröffentlicht	Versionshinweise
1.4	11. Dez 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox/releases/tag/1.4	Herunterladen

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das 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} }