Kurtosis and negentropy investigation of myo electric signals during different MVCs

Ganesh R. Naik; Dinesh K. Kumar; Sridhar P. Arjunan

doi:10.1109/BRC.2011.5740669

Kurtosis and negentropy investigation of myo electric signals during different MVCs

Ganesh R. Naik, Dinesh K. Kumar, Sridhar P. Arjunan

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

16 Citations (Scopus)

Abstract

This research deals with computing the non-Gaussianity in Surface Electromyogram signal (sEMG) using Negative entropy and Kurtosis values. The signal was acquired from three different finger and wrist actions at four different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density function (pdf) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) pdf measures tends to be Gaussian process. The above measures were verified by computing the kurtosis values for different MVCs.

Original language	English
Title of host publication	Proceedings of 2011 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC2011), 6-8 January 2011, Vitoria, Brazil
Publisher	IEEE
Pages	40-43
Number of pages	4
ISBN (Print)	9781424482122
DOIs	https://doi.org/10.1109/BRC.2011.5740669
Publication status	Published - 2011
Event	ISSNIP Biosignals and Biorobotics Conference - Duration: 9 Jan 2012 → …

Conference

Conference	ISSNIP Biosignals and Biorobotics Conference
Period	9/01/12 → …

Keywords

Gaussian processes
electromyography
robotics

Access to Document

10.1109/BRC.2011.5740669

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@inproceedings{0eab54122817437eb34470493be3fd03,

title = "Kurtosis and negentropy investigation of myo electric signals during different MVCs",

abstract = "This research deals with computing the non-Gaussianity in Surface Electromyogram signal (sEMG) using Negative entropy and Kurtosis values. The signal was acquired from three different finger and wrist actions at four different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density function (pdf) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) pdf measures tends to be Gaussian process. The above measures were verified by computing the kurtosis values for different MVCs.",

keywords = "Gaussian processes, electromyography, robotics",

author = "Naik, {Ganesh R.} and Kumar, {Dinesh K.} and Arjunan, {Sridhar P.}",

year = "2011",

doi = "10.1109/BRC.2011.5740669",

language = "English",

isbn = "9781424482122",

pages = "40--43",

booktitle = "Proceedings of 2011 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC2011), 6-8 January 2011, Vitoria, Brazil",

publisher = "IEEE",

note = "ISSNIP Biosignals and Biorobotics Conference ; Conference date: 09-01-2012",

}

Naik, GR, Kumar, DK & Arjunan, SP 2011, Kurtosis and negentropy investigation of myo electric signals during different MVCs. in Proceedings of 2011 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC2011), 6-8 January 2011, Vitoria, Brazil. IEEE, pp. 40-43, ISSNIP Biosignals and Biorobotics Conference, 9/01/12. https://doi.org/10.1109/BRC.2011.5740669

Kurtosis and negentropy investigation of myo electric signals during different MVCs. / Naik, Ganesh R.; Kumar, Dinesh K.; Arjunan, Sridhar P.
Proceedings of 2011 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC2011), 6-8 January 2011, Vitoria, Brazil. IEEE, 2011. p. 40-43.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Kurtosis and negentropy investigation of myo electric signals during different MVCs

AU - Naik, Ganesh R.

AU - Kumar, Dinesh K.

AU - Arjunan, Sridhar P.

PY - 2011

Y1 - 2011

N2 - This research deals with computing the non-Gaussianity in Surface Electromyogram signal (sEMG) using Negative entropy and Kurtosis values. The signal was acquired from three different finger and wrist actions at four different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density function (pdf) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) pdf measures tends to be Gaussian process. The above measures were verified by computing the kurtosis values for different MVCs.

AB - This research deals with computing the non-Gaussianity in Surface Electromyogram signal (sEMG) using Negative entropy and Kurtosis values. The signal was acquired from three different finger and wrist actions at four different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density function (pdf) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) pdf measures tends to be Gaussian process. The above measures were verified by computing the kurtosis values for different MVCs.

KW - Gaussian processes

KW - electromyography

KW - robotics

UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:42710

U2 - 10.1109/BRC.2011.5740669

DO - 10.1109/BRC.2011.5740669

M3 - Conference Paper

SN - 9781424482122

SP - 40

EP - 43

BT - Proceedings of 2011 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC2011), 6-8 January 2011, Vitoria, Brazil

PB - IEEE

T2 - ISSNIP Biosignals and Biorobotics Conference

Y2 - 9 January 2012

ER -

Kurtosis and negentropy investigation of myo electric signals during different MVCs

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Keywords

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