Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal

Maged S. Al-Quraishi; Irraivan Elamvazuthi; Siti Asmah Daud; S. Parasuraman; Alberto Borboni

doi:10.1109/ICIAS.2018.8540632

Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal

Maged S. Al-Quraishi
, Irraivan Elamvazuthi^*
, Siti Asmah Daud
, S. Parasuraman
, Alberto Borboni

^*Corresponding author for this work

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

2 Scopus citations

Abstract

Electromyography (EMG) based control is growing to be a part and parcel of the assistive devices technique today. Nonetheless, high sensitivity of EMG to the muscular fatigue affect the performance of EMG signal as a control input to the assistive devices. In this paper, the influences of muscular fatigue on the ankle joint motion recognition have been investigated. Three shank muscles and two ankle joint movements have been involved in this experiment. In order to assess the muscular fatigue on the motion recognition based on EMG signal, Multilayer Percepteron (MLP) and K Nearest Neighborhood (kNN) were employed. The outcomes of this experiment showed the drastic change in the recognition accuracy of the two ankle joint movements before and after inducing muscular fatigue. The overall classification accuracies for all subjects before fatigue were 97.7% and 97.4% for MLP and kNN respectively. Whereas, the overall classification accuracies for all subjects after fatigue were 92.89% and 91.09% for MLP and kNN respectively.

Original language	English
Title of host publication	International Conference on Intelligent and Advanced System, ICIAS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538672693
DOIs	https://doi.org/10.1109/ICIAS.2018.8540632
State	Published - 19 Nov 2018
Externally published	Yes

Publication series

Name	International Conference on Intelligent and Advanced System, ICIAS 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Ankle joint
Electromyography
Fatigue
Pattern Recognition

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Energy Engineering and Power Technology
Health Informatics

Access to Document

10.1109/ICIAS.2018.8540632

Cite this

Al-Quraishi, M. S., Elamvazuthi, I., Daud, S. A., Parasuraman, S., & Borboni, A. (2018). Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal. In International Conference on Intelligent and Advanced System, ICIAS 2018 Article 8540632 (International Conference on Intelligent and Advanced System, ICIAS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIAS.2018.8540632

Al-Quraishi, Maged S. ; Elamvazuthi, Irraivan ; Daud, Siti Asmah et al. / Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal. International Conference on Intelligent and Advanced System, ICIAS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (International Conference on Intelligent and Advanced System, ICIAS 2018).

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title = "Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal",

abstract = "Electromyography (EMG) based control is growing to be a part and parcel of the assistive devices technique today. Nonetheless, high sensitivity of EMG to the muscular fatigue affect the performance of EMG signal as a control input to the assistive devices. In this paper, the influences of muscular fatigue on the ankle joint motion recognition have been investigated. Three shank muscles and two ankle joint movements have been involved in this experiment. In order to assess the muscular fatigue on the motion recognition based on EMG signal, Multilayer Percepteron (MLP) and K Nearest Neighborhood (kNN) were employed. The outcomes of this experiment showed the drastic change in the recognition accuracy of the two ankle joint movements before and after inducing muscular fatigue. The overall classification accuracies for all subjects before fatigue were 97.7\% and 97.4\% for MLP and kNN respectively. Whereas, the overall classification accuracies for all subjects after fatigue were 92.89\% and 91.09\% for MLP and kNN respectively.",

keywords = "Ankle joint, Electromyography, Fatigue, Pattern Recognition",

author = "Al-Quraishi, \{Maged S.\} and Irraivan Elamvazuthi and Daud, \{Siti Asmah\} and S. Parasuraman and Alberto Borboni",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.",

year = "2018",

month = nov,

day = "19",

doi = "10.1109/ICIAS.2018.8540632",

language = "English",

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Al-Quraishi, MS, Elamvazuthi, I, Daud, SA, Parasuraman, S & Borboni, A 2018, Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal. in International Conference on Intelligent and Advanced System, ICIAS 2018., 8540632, International Conference on Intelligent and Advanced System, ICIAS 2018, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICIAS.2018.8540632

Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal. / Al-Quraishi, Maged S.; Elamvazuthi, Irraivan; Daud, Siti Asmah et al.
International Conference on Intelligent and Advanced System, ICIAS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8540632 (International Conference on Intelligent and Advanced System, ICIAS 2018).

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

TY - GEN

T1 - Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal

AU - Al-Quraishi, Maged S.

AU - Elamvazuthi, Irraivan

AU - Daud, Siti Asmah

AU - Parasuraman, S.

AU - Borboni, Alberto

PY - 2018/11/19

Y1 - 2018/11/19

N2 - Electromyography (EMG) based control is growing to be a part and parcel of the assistive devices technique today. Nonetheless, high sensitivity of EMG to the muscular fatigue affect the performance of EMG signal as a control input to the assistive devices. In this paper, the influences of muscular fatigue on the ankle joint motion recognition have been investigated. Three shank muscles and two ankle joint movements have been involved in this experiment. In order to assess the muscular fatigue on the motion recognition based on EMG signal, Multilayer Percepteron (MLP) and K Nearest Neighborhood (kNN) were employed. The outcomes of this experiment showed the drastic change in the recognition accuracy of the two ankle joint movements before and after inducing muscular fatigue. The overall classification accuracies for all subjects before fatigue were 97.7% and 97.4% for MLP and kNN respectively. Whereas, the overall classification accuracies for all subjects after fatigue were 92.89% and 91.09% for MLP and kNN respectively.

AB - Electromyography (EMG) based control is growing to be a part and parcel of the assistive devices technique today. Nonetheless, high sensitivity of EMG to the muscular fatigue affect the performance of EMG signal as a control input to the assistive devices. In this paper, the influences of muscular fatigue on the ankle joint motion recognition have been investigated. Three shank muscles and two ankle joint movements have been involved in this experiment. In order to assess the muscular fatigue on the motion recognition based on EMG signal, Multilayer Percepteron (MLP) and K Nearest Neighborhood (kNN) were employed. The outcomes of this experiment showed the drastic change in the recognition accuracy of the two ankle joint movements before and after inducing muscular fatigue. The overall classification accuracies for all subjects before fatigue were 97.7% and 97.4% for MLP and kNN respectively. Whereas, the overall classification accuracies for all subjects after fatigue were 92.89% and 91.09% for MLP and kNN respectively.

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BT - International Conference on Intelligent and Advanced System, ICIAS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Al-Quraishi MS, Elamvazuthi I, Daud SA, Parasuraman S, Borboni A. Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal. In International Conference on Intelligent and Advanced System, ICIAS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8540632. (International Conference on Intelligent and Advanced System, ICIAS 2018). doi: 10.1109/ICIAS.2018.8540632

Influences of Muscular Fatigue on Ankle Joint Motion Recognition Based on Electromyography Signal

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this