Effect of VMD decomposition of soleus muscle EMG in SVM classification

V. M. Akhil; Jobin Varghese; P. K. Rajendrakumar; Sivanandan K S

doi:10.1109/ICACCP.2019.8882900

Effect of VMD decomposition of soleus muscle EMG in SVM classification

V. M. Akhil, Jobin Varghese, P. K. Rajendrakumar, Sivanandan K S

Department of Biomedical Engineering, Manipal Institute of Technology, Manipal

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

1 Citation (Scopus)

Abstract

Electromyography (EMG) is widely used for diagnosis in the field of bio-medical research. The EMG signal from the soleus muscle is utilized in this study to understand the effect of variational mode decomposition (VMD) in signal classification. In this work forward and backward walking in even and uneven surfaces with inclinations of 0° and 10° were considered. Ten time domain features were extracted from both raw surface EMG signal, and VMD decomposed EMG signal. Scatter plot of features in all walking condition is analyzed to understand the variation within the scatter group. The features extracted from VMD based components were shown to perform better in accuracy during Support Vector Machines (SVM) classification than the raw signal.

Original language	English
Title of host publication	2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538679890
DOIs	https://doi.org/10.1109/ICACCP.2019.8882900
Publication status	Published - 02-2019
Event	2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019 - Gangtok, Sikkim, India Duration: 25-02-2018 → 28-02-2018

Publication series

Name	2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019

Conference

Conference	2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019
Country/Territory	India
City	Gangtok, Sikkim
Period	25-02-18 → 28-02-18

All Science Journal Classification (ASJC) codes

Signal Processing
Artificial Intelligence
Computer Networks and Communications
Instrumentation

Access to Document

10.1109/ICACCP.2019.8882900

Cite this

Akhil, V. M., Varghese, J., Rajendrakumar, P. K., & K S, S. (2019). Effect of VMD decomposition of soleus muscle EMG in SVM classification. In 2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019 [8882900] (2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCP.2019.8882900

Akhil, V. M. ; Varghese, Jobin ; Rajendrakumar, P. K. et al. / Effect of VMD decomposition of soleus muscle EMG in SVM classification. 2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019).

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title = "Effect of VMD decomposition of soleus muscle EMG in SVM classification",

abstract = "Electromyography (EMG) is widely used for diagnosis in the field of bio-medical research. The EMG signal from the soleus muscle is utilized in this study to understand the effect of variational mode decomposition (VMD) in signal classification. In this work forward and backward walking in even and uneven surfaces with inclinations of 0° and 10° were considered. Ten time domain features were extracted from both raw surface EMG signal, and VMD decomposed EMG signal. Scatter plot of features in all walking condition is analyzed to understand the variation within the scatter group. The features extracted from VMD based components were shown to perform better in accuracy during Support Vector Machines (SVM) classification than the raw signal.",

author = "Akhil, {V. M.} and Jobin Varghese and Rajendrakumar, {P. K.} and {K S}, Sivanandan",

year = "2019",

month = feb,

doi = "10.1109/ICACCP.2019.8882900",

language = "English",

series = "2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019",

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

booktitle = "2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019",

address = "United States",

note = "2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019 ; Conference date: 25-02-2018 Through 28-02-2018",

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Akhil, VM, Varghese, J, Rajendrakumar, PK & K S, S 2019, Effect of VMD decomposition of soleus muscle EMG in SVM classification. in 2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019., 8882900, 2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019, Gangtok, Sikkim, India, 25-02-18. https://doi.org/10.1109/ICACCP.2019.8882900

Effect of VMD decomposition of soleus muscle EMG in SVM classification. / Akhil, V. M.; Varghese, Jobin; Rajendrakumar, P. K. et al.
2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8882900 (2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019).

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

TY - GEN

T1 - Effect of VMD decomposition of soleus muscle EMG in SVM classification

AU - Akhil, V. M.

AU - Varghese, Jobin

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N2 - Electromyography (EMG) is widely used for diagnosis in the field of bio-medical research. The EMG signal from the soleus muscle is utilized in this study to understand the effect of variational mode decomposition (VMD) in signal classification. In this work forward and backward walking in even and uneven surfaces with inclinations of 0° and 10° were considered. Ten time domain features were extracted from both raw surface EMG signal, and VMD decomposed EMG signal. Scatter plot of features in all walking condition is analyzed to understand the variation within the scatter group. The features extracted from VMD based components were shown to perform better in accuracy during Support Vector Machines (SVM) classification than the raw signal.

AB - Electromyography (EMG) is widely used for diagnosis in the field of bio-medical research. The EMG signal from the soleus muscle is utilized in this study to understand the effect of variational mode decomposition (VMD) in signal classification. In this work forward and backward walking in even and uneven surfaces with inclinations of 0° and 10° were considered. Ten time domain features were extracted from both raw surface EMG signal, and VMD decomposed EMG signal. Scatter plot of features in all walking condition is analyzed to understand the variation within the scatter group. The features extracted from VMD based components were shown to perform better in accuracy during Support Vector Machines (SVM) classification than the raw signal.

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BT - 2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019

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Akhil VM, Varghese J, Rajendrakumar PK, K S S. Effect of VMD decomposition of soleus muscle EMG in SVM classification. In 2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8882900. (2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019). doi: 10.1109/ICACCP.2019.8882900

Effect of VMD decomposition of soleus muscle EMG in SVM classification

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