Slow-time changes in human muscle fatigue are fully represented in movement kinematics

Song Miao, David B. Segala, Jonathan Dingwell, David Chelidze

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

Abstract

Muscle fatigue is exhibited in individuals who partake in repetitive movements for an extensive duration of time. The objective of this study was to identify correlation, if any, between movement kinematics and muscle electrical activity (EMG). Movement kinematics and EMG signals were measured and recorded from the lower extremities of stationary elite cyclists. Standard statistical metrics (SSM) and phase space warping (PSW) based features were extracted from the recorded fast-time time series for consecutive intermediate time intervals. The SSM based features were composed of higher moments, fractal dimension, correlation sum, power spectral density, and cross-correlation. The PSW based features were subject to quantifying shorttime differences between the fatigued and unfatigued reconstructed phase spaces. The slow-time manifolds describing global fatigue dynamics in these feature spaces were extracted using smooth orthogonal decomposition (SOD). Mean and median frequencies from the EMG data were calculated to describe the local fatigue dynamics in each muscle. There were very close correlations between the EMG and kinematics data based global fatigue features. Also, the 4 and 5 dimensional slow time manifolds (corresponding to PSW and SSM based features, respectively) fully represented the local fatigue dynamics in all the muscles as described by the EMG data. Therefore, for this particular context, the fatigue information present in the standard EMG analysis was fully represented in the SOD based slowtime features extracted from the kinematic data. Furthermore, the SOD based analysis gave estimates of effective dimensionality of muscle fatigue dynamics.

Original languageEnglish (US)
Title of host publication2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007
Pages679-688
Number of pages10
DOIs
StatePublished - Jun 13 2008
Event21st Biennial Conference on Mechanical Vibration and Noise, presented at - 2007 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2007 - Las Vegas, NV, United States
Duration: Sep 4 2007Sep 7 2007

Publication series

Name2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007
Volume1 PART A

Other

Other21st Biennial Conference on Mechanical Vibration and Noise, presented at - 2007 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2007
CountryUnited States
CityLas Vegas, NV
Period9/4/079/7/07

Fingerprint

Time Change
Muscle
Fatigue
Kinematics
Fatigue of materials
Warping
Orthogonal Decomposition
Phase Space
Decomposition
Metric
Power Spectral Density
Power spectral density
Fractal dimension
Cross-correlation
Movement
Human
Feature Space
Fractal Dimension
Dimensionality
Metric space

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Mechanical Engineering
  • Modeling and Simulation

Cite this

Miao, S., Segala, D. B., Dingwell, J., & Chelidze, D. (2008). Slow-time changes in human muscle fatigue are fully represented in movement kinematics. In 2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007 (pp. 679-688). (2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007; Vol. 1 PART A). https://doi.org/10.1115/DETC2007-35173
Miao, Song ; Segala, David B. ; Dingwell, Jonathan ; Chelidze, David. / Slow-time changes in human muscle fatigue are fully represented in movement kinematics. 2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007. 2008. pp. 679-688 (2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007).
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abstract = "Muscle fatigue is exhibited in individuals who partake in repetitive movements for an extensive duration of time. The objective of this study was to identify correlation, if any, between movement kinematics and muscle electrical activity (EMG). Movement kinematics and EMG signals were measured and recorded from the lower extremities of stationary elite cyclists. Standard statistical metrics (SSM) and phase space warping (PSW) based features were extracted from the recorded fast-time time series for consecutive intermediate time intervals. The SSM based features were composed of higher moments, fractal dimension, correlation sum, power spectral density, and cross-correlation. The PSW based features were subject to quantifying shorttime differences between the fatigued and unfatigued reconstructed phase spaces. The slow-time manifolds describing global fatigue dynamics in these feature spaces were extracted using smooth orthogonal decomposition (SOD). Mean and median frequencies from the EMG data were calculated to describe the local fatigue dynamics in each muscle. There were very close correlations between the EMG and kinematics data based global fatigue features. Also, the 4 and 5 dimensional slow time manifolds (corresponding to PSW and SSM based features, respectively) fully represented the local fatigue dynamics in all the muscles as described by the EMG data. Therefore, for this particular context, the fatigue information present in the standard EMG analysis was fully represented in the SOD based slowtime features extracted from the kinematic data. Furthermore, the SOD based analysis gave estimates of effective dimensionality of muscle fatigue dynamics.",
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Miao, S, Segala, DB, Dingwell, J & Chelidze, D 2008, Slow-time changes in human muscle fatigue are fully represented in movement kinematics. in 2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007. 2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007, vol. 1 PART A, pp. 679-688, 21st Biennial Conference on Mechanical Vibration and Noise, presented at - 2007 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2007, Las Vegas, NV, United States, 9/4/07. https://doi.org/10.1115/DETC2007-35173

Slow-time changes in human muscle fatigue are fully represented in movement kinematics. / Miao, Song; Segala, David B.; Dingwell, Jonathan; Chelidze, David.

2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007. 2008. p. 679-688 (2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007; Vol. 1 PART A).

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

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Miao S, Segala DB, Dingwell J, Chelidze D. Slow-time changes in human muscle fatigue are fully represented in movement kinematics. In 2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007. 2008. p. 679-688. (2007 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2007). https://doi.org/10.1115/DETC2007-35173