sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification

Hiba Hellara; Rim Barioul; Ayoub Choura; Salwa Sahnoun; Ahmed Fakhfakh; Dhouha Bouchaala; Mohamed Deriche; Olfa Kanoun

doi:10.1109/SSD54932.2022.9955800

sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification

Hiba Hellara
, Rim Barioul
, Ayoub Choura
, Salwa Sahnoun
, Ahmed Fakhfakh
, Dhouha Bouchaala
, Mohamed Deriche
, Olfa Kanoun

University of Sfax

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Swarm intelligence algorithms are widely used for wrapper feature selection applications. Such algorithms have some limitations on exploration, exploitation, and local optima convergence. This paper considers the enhanced approaches of the Salp Swarm Algorithm (SSA) for feature selection from an sEMG dataset. In this paper, four different chaotic maps, namely: circle, tent, piecewise, and logistic map, are used to improve the balance between exploration and exploitation in SSA. After running the approaches twenty times, we compare these maps according to the average classification accuracy values, execution time, and the number of selected features. Results prove that the piecewise map shows the best performance by giving 79.80% accuracy in short time with a small number of selected features and good convergence speed.

Original language	English
Title of host publication	2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	622-628
Number of pages	7
ISBN (Electronic)	9781665471084
DOIs	https://doi.org/10.1109/SSD54932.2022.9955800
State	Published - 2022
Externally published	Yes
Event	19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022 - Setif, Algeria Duration: 6 May 2022 → 10 May 2022

Publication series

Name	2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

Conference

Conference	19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022
Country/Territory	Algeria
City	Setif
Period	6/05/22 → 10/05/22

Keywords

Chaotic maps
Classification
Electromyography
Feature Selection
Optimization
Salp Swarm Algorithm
Wrappers

Access to Document

10.1109/SSD54932.2022.9955800

Cite this

Hellara, H., Barioul, R., Choura, A., Sahnoun, S., Fakhfakh, A., Bouchaala, D., Deriche, M., & Kanoun, O. (2022). sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification. In 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022 (pp. 622-628). (2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSD54932.2022.9955800

Hellara, Hiba ; Barioul, Rim ; Choura, Ayoub et al. / sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification. 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 622-628 (2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022).

@inproceedings{c22ea1f668a44a9cbd1a665fda220f83,

title = "sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification",

abstract = "Swarm intelligence algorithms are widely used for wrapper feature selection applications. Such algorithms have some limitations on exploration, exploitation, and local optima convergence. This paper considers the enhanced approaches of the Salp Swarm Algorithm (SSA) for feature selection from an sEMG dataset. In this paper, four different chaotic maps, namely: circle, tent, piecewise, and logistic map, are used to improve the balance between exploration and exploitation in SSA. After running the approaches twenty times, we compare these maps according to the average classification accuracy values, execution time, and the number of selected features. Results prove that the piecewise map shows the best performance by giving 79.80\% accuracy in short time with a small number of selected features and good convergence speed.",

keywords = "Chaotic maps, Classification, Electromyography, Feature Selection, Optimization, Salp Swarm Algorithm, Wrappers",

author = "Hiba Hellara and Rim Barioul and Ayoub Choura and Salwa Sahnoun and Ahmed Fakhfakh and Dhouha Bouchaala and Mohamed Deriche and Olfa Kanoun",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022 ; Conference date: 06-05-2022 Through 10-05-2022",

year = "2022",

doi = "10.1109/SSD54932.2022.9955800",

language = "English",

series = "2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "622--628",

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}

Hellara, H, Barioul, R, Choura, A, Sahnoun, S, Fakhfakh, A, Bouchaala, D, Deriche, M & Kanoun, O 2022, sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification. in 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022. 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022, Institute of Electrical and Electronics Engineers Inc., pp. 622-628, 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022, Setif, Algeria, 6/05/22. https://doi.org/10.1109/SSD54932.2022.9955800

sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification. / Hellara, Hiba; Barioul, Rim; Choura, Ayoub et al.
2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 622-628 (2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification

AU - Hellara, Hiba

AU - Barioul, Rim

AU - Choura, Ayoub

AU - Sahnoun, Salwa

AU - Fakhfakh, Ahmed

AU - Bouchaala, Dhouha

AU - Deriche, Mohamed

AU - Kanoun, Olfa

PY - 2022

Y1 - 2022

N2 - Swarm intelligence algorithms are widely used for wrapper feature selection applications. Such algorithms have some limitations on exploration, exploitation, and local optima convergence. This paper considers the enhanced approaches of the Salp Swarm Algorithm (SSA) for feature selection from an sEMG dataset. In this paper, four different chaotic maps, namely: circle, tent, piecewise, and logistic map, are used to improve the balance between exploration and exploitation in SSA. After running the approaches twenty times, we compare these maps according to the average classification accuracy values, execution time, and the number of selected features. Results prove that the piecewise map shows the best performance by giving 79.80% accuracy in short time with a small number of selected features and good convergence speed.

AB - Swarm intelligence algorithms are widely used for wrapper feature selection applications. Such algorithms have some limitations on exploration, exploitation, and local optima convergence. This paper considers the enhanced approaches of the Salp Swarm Algorithm (SSA) for feature selection from an sEMG dataset. In this paper, four different chaotic maps, namely: circle, tent, piecewise, and logistic map, are used to improve the balance between exploration and exploitation in SSA. After running the approaches twenty times, we compare these maps according to the average classification accuracy values, execution time, and the number of selected features. Results prove that the piecewise map shows the best performance by giving 79.80% accuracy in short time with a small number of selected features and good convergence speed.

KW - Chaotic maps

KW - Classification

KW - Electromyography

KW - Feature Selection

KW - Optimization

KW - Salp Swarm Algorithm

KW - Wrappers

UR - https://www.scopus.com/pages/publications/85137792498

U2 - 10.1109/SSD54932.2022.9955800

DO - 10.1109/SSD54932.2022.9955800

M3 - Conference contribution

AN - SCOPUS:85137792498

T3 - 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

SP - 622

EP - 628

BT - 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

Y2 - 6 May 2022 through 10 May 2022

ER -

Hellara H, Barioul R, Choura A, Sahnoun S, Fakhfakh A, Bouchaala D et al. sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification. In 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 622-628. (2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022). doi: 10.1109/SSD54932.2022.9955800

sEMG Features Selection by a Chaotic Salp Swarm Algorithm for Hand Gestures Classification

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