Determination of muscle fatigue in SEMG signal using empirical mode decomposition

Rubana H. Chowdhury, Md. Mamun Ibne Reaz, M. A M Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Muscle fatigue is defined as the long lasting deterioration of a performance of the human operator to create force. Walking fast can cause muscle fatigue, which is unhealthy and it is incurable when the level of fatigue is high. Muscle fatigue is a well-known research area. In order to completely comprehend the idea many research have been done on different type of muscle fatigue. There are many spectral variables that can be used to determine muscle fatigue during gait. Out of these variables, the amplitude and frequency of the surface EMG signal provide a more accurate reflection of motor unit pattern. In this research, Empirical mode decomposition (EMD) and wavelet Transform applied to the surface EMG (SEMG) signal for realizing the fatiguing contraction during human walking exercise. In this study, RMS, IAV and AIF values were used as spectral variable, which extensively identifies the difference between fatigue and normal muscle when using EMD method compared with other different wavelet functions (WFs). Furthermore, the outcome also proves that, the SEMG amplitude and frequency momentously changes from rest position to maximum contraction position. This research reports on the effectiveness of EMD-based filtering method applied to the surface EMG (SEMG) signal as a means of achieving reliable discrimination of the muscle fatigue.

Original languageEnglish
Title of host publicationIECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet"
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages932-937
Number of pages6
ISBN (Print)9781479940844
DOIs
Publication statusPublished - 23 Feb 2015
Event3rd IEEE Conference on Biomedical Engineering and Sciences, IECBES 2014 - Kuala Lumpur
Duration: 8 Dec 201410 Dec 2014

Other

Other3rd IEEE Conference on Biomedical Engineering and Sciences, IECBES 2014
CityKuala Lumpur
Period8/12/1410/12/14

Fingerprint

Muscle
Fatigue of materials
Decomposition
Wavelet transforms
Deterioration

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Chowdhury, R. H., Ibne Reaz, M. M., & Ali, M. A. M. (2015). Determination of muscle fatigue in SEMG signal using empirical mode decomposition. In IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet" (pp. 932-937). [7047649] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECBES.2014.7047649

Determination of muscle fatigue in SEMG signal using empirical mode decomposition. / Chowdhury, Rubana H.; Ibne Reaz, Md. Mamun; Ali, M. A M.

IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet". Institute of Electrical and Electronics Engineers Inc., 2015. p. 932-937 7047649.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chowdhury, RH, Ibne Reaz, MM & Ali, MAM 2015, Determination of muscle fatigue in SEMG signal using empirical mode decomposition. in IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet"., 7047649, Institute of Electrical and Electronics Engineers Inc., pp. 932-937, 3rd IEEE Conference on Biomedical Engineering and Sciences, IECBES 2014, Kuala Lumpur, 8/12/14. https://doi.org/10.1109/IECBES.2014.7047649
Chowdhury RH, Ibne Reaz MM, Ali MAM. Determination of muscle fatigue in SEMG signal using empirical mode decomposition. In IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet". Institute of Electrical and Electronics Engineers Inc. 2015. p. 932-937. 7047649 https://doi.org/10.1109/IECBES.2014.7047649
Chowdhury, Rubana H. ; Ibne Reaz, Md. Mamun ; Ali, M. A M. / Determination of muscle fatigue in SEMG signal using empirical mode decomposition. IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet". Institute of Electrical and Electronics Engineers Inc., 2015. pp. 932-937
@inproceedings{96649d1e68ee4aa1b368c87bd8056f39,
title = "Determination of muscle fatigue in SEMG signal using empirical mode decomposition",
abstract = "Muscle fatigue is defined as the long lasting deterioration of a performance of the human operator to create force. Walking fast can cause muscle fatigue, which is unhealthy and it is incurable when the level of fatigue is high. Muscle fatigue is a well-known research area. In order to completely comprehend the idea many research have been done on different type of muscle fatigue. There are many spectral variables that can be used to determine muscle fatigue during gait. Out of these variables, the amplitude and frequency of the surface EMG signal provide a more accurate reflection of motor unit pattern. In this research, Empirical mode decomposition (EMD) and wavelet Transform applied to the surface EMG (SEMG) signal for realizing the fatiguing contraction during human walking exercise. In this study, RMS, IAV and AIF values were used as spectral variable, which extensively identifies the difference between fatigue and normal muscle when using EMD method compared with other different wavelet functions (WFs). Furthermore, the outcome also proves that, the SEMG amplitude and frequency momentously changes from rest position to maximum contraction position. This research reports on the effectiveness of EMD-based filtering method applied to the surface EMG (SEMG) signal as a means of achieving reliable discrimination of the muscle fatigue.",
author = "Chowdhury, {Rubana H.} and {Ibne Reaz}, {Md. Mamun} and Ali, {M. A M}",
year = "2015",
month = "2",
day = "23",
doi = "10.1109/IECBES.2014.7047649",
language = "English",
isbn = "9781479940844",
pages = "932--937",
booktitle = "IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: {"}Miri, Where Engineering in Medicine and Biology and Humanity Meet{"}",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Determination of muscle fatigue in SEMG signal using empirical mode decomposition

AU - Chowdhury, Rubana H.

AU - Ibne Reaz, Md. Mamun

AU - Ali, M. A M

PY - 2015/2/23

Y1 - 2015/2/23

N2 - Muscle fatigue is defined as the long lasting deterioration of a performance of the human operator to create force. Walking fast can cause muscle fatigue, which is unhealthy and it is incurable when the level of fatigue is high. Muscle fatigue is a well-known research area. In order to completely comprehend the idea many research have been done on different type of muscle fatigue. There are many spectral variables that can be used to determine muscle fatigue during gait. Out of these variables, the amplitude and frequency of the surface EMG signal provide a more accurate reflection of motor unit pattern. In this research, Empirical mode decomposition (EMD) and wavelet Transform applied to the surface EMG (SEMG) signal for realizing the fatiguing contraction during human walking exercise. In this study, RMS, IAV and AIF values were used as spectral variable, which extensively identifies the difference between fatigue and normal muscle when using EMD method compared with other different wavelet functions (WFs). Furthermore, the outcome also proves that, the SEMG amplitude and frequency momentously changes from rest position to maximum contraction position. This research reports on the effectiveness of EMD-based filtering method applied to the surface EMG (SEMG) signal as a means of achieving reliable discrimination of the muscle fatigue.

AB - Muscle fatigue is defined as the long lasting deterioration of a performance of the human operator to create force. Walking fast can cause muscle fatigue, which is unhealthy and it is incurable when the level of fatigue is high. Muscle fatigue is a well-known research area. In order to completely comprehend the idea many research have been done on different type of muscle fatigue. There are many spectral variables that can be used to determine muscle fatigue during gait. Out of these variables, the amplitude and frequency of the surface EMG signal provide a more accurate reflection of motor unit pattern. In this research, Empirical mode decomposition (EMD) and wavelet Transform applied to the surface EMG (SEMG) signal for realizing the fatiguing contraction during human walking exercise. In this study, RMS, IAV and AIF values were used as spectral variable, which extensively identifies the difference between fatigue and normal muscle when using EMD method compared with other different wavelet functions (WFs). Furthermore, the outcome also proves that, the SEMG amplitude and frequency momentously changes from rest position to maximum contraction position. This research reports on the effectiveness of EMD-based filtering method applied to the surface EMG (SEMG) signal as a means of achieving reliable discrimination of the muscle fatigue.

UR - http://www.scopus.com/inward/record.url?scp=84925610404&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84925610404&partnerID=8YFLogxK

U2 - 10.1109/IECBES.2014.7047649

DO - 10.1109/IECBES.2014.7047649

M3 - Conference contribution

AN - SCOPUS:84925610404

SN - 9781479940844

SP - 932

EP - 937

BT - IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet"

PB - Institute of Electrical and Electronics Engineers Inc.

ER -