EMG Feature Extraction Toolbox

Version 1.4 (17,4 ko) par 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/

Suivre

4.4

(8)

4K téléchargements

Mise à jour 11 déc. 2020

Afficher la licence sur 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

Citation pour cette source

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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Compatibilité avec les versions de MATLAB

Créé avec R2018a

Compatible avec toutes les versions

Plateformes compatibles

Windows macOS Linux

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Remerciements

A inspiré : Identify Arm Motions Using EMG Signals and Deep Learning.

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Version	Publié le	Notes de version
1.4	11 déc. 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox/releases/tag/1.4	Télécharger

Pour consulter ou signaler des problèmes liés à ce module complémentaire GitHub, accédez au dépôt GitHub.

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} }