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Research Papers

Measurement and Validation of Exercise-Induced Fatigue Through Inertial Motion Analysis

[+] Author and Article Information
Sina Ameli

School of Electrical, Computer
and Telecommunication (SECTE),
Faculty of Engineering,
University of Wollongong,
Wollongong 2522, NSW, Australia
e-mail: sameli@uow.edu.au

Fazel Naghdy, David Stirling, Golshah Naghdy

School of Electrical, Computer
and Telecommunication (SECTE),
Faculty of Engineering,
University of Wollongong,
Wollongong 2522, NSW, Australia

Morteza Aghmesheh

Wollongong Hospital,
Illawarra Cancer Care Centre,
Wollongong 2500, NSW, Australia

Ryan Anthony, Peter McLennan, Gregory Peoples

Faculty of Science, Medicine
and Health (SMAH),
Graduate School of Medicine,
University of Wollongong,
Wollongong 2522, NSW, Australia

1Corresponding author.

Manuscript received September 10, 2017; final manuscript received January 30, 2018; published online March 27, 2018. Editor: Ahmed Al-Jumaily.

ASME J of Medical Diagnostics 1(2), 021007 (Mar 27, 2018) (11 pages) Paper No: JESMDT-17-2035; doi: 10.1115/1.4039211 History: Received September 10, 2017; Revised January 30, 2018

Exercise-induced fatigue evolves from the initiation of physical work. Nonetheless, the development of an objective method for detecting fatigue based on variation in ambulatory motion parameters measured during exercise is yet to be explored. In this study, the ambulatory motion parameters consisting of kinematic parameters of 23 body segments in addition to muscle tissue oxygen saturation (SmO2), heart rate, and vertical work of eight healthy male subjects during stair climbing tests (SCT) were measured before and after a fatigue protocol utilizing Wingate cycling test. The impacts of fatigue on ambulatory motion and postural behaviors were analyzed using an unsupervised machine learning method classifying angular joint motions. The average of total distance traveled by subjects and the overall body postural behavior showed about 25% decline and 90% variation after fatigue protocol, respectively. Also, higher relative desaturation in SCT1 −64.0 (1.1) compared SCT2 −54.8 (1.1) was measured. Measurements of differences in motion postural states and metabolic indexes after exercises-induced fatigue proved a strong correlation which validates the advantages of inertial motion analysis method for fatigue assessment.

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Copyright © 2018 by ASME
Topics: Fatigue , Kinematics
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Figures

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Fig. 1

The schematic diagram of experimental procedure

Grahic Jump Location
Fig. 2

The experimental setup during SCT: (a) inertial motion capture: Moven®, light weight motion capture straps housing a network of 17 MTx inertial sensors distribution of MTx sensors (Adapted from Xsens Technologies, 2007); (b) the biomechanical model representation of subject during SCT; (c) implementation of MOXY and inertial sensors during SCT; and (d) the real-time joint angle data shown in mvn studio software

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Fig. 3

The power output of subjects during Wingate cycling test. (a) Mean power output (w) for each individual subject (1–8) in the first and last 30 s Wingate cycling bout. *P < 0.05 group mean first bout versus last bout. (b) Peak power output (w) for each individual subject (1–8) before (pre) and after (post) the fatigue protocol (repeat bout 6 s Wingate). *P < 0.05 group mean pre versus post fatigue.

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Fig. 4

The difference in vertical work before and after fatigue protocol. Vertical work (positive) (J) completed during stair climb test for each individual subject (1–8) before (pre) and after (post) the fatigue protocol (repeat bout 30 s Wingate). *P < 0.05 group mean pre versus post fatigue.

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Fig. 5

Twitch factors and box plots of GMM clusters of all body joint angles for eight subjects during SCTs before and after fatigue protocol: (a) the box plot and TF of GMM sequences of first subject during two SCTs; (b) the box plot and TF of GMM sequences of second subject during two SCTs; (c) the box plot and TF of GMM sequences of third subject during two SCTs; (d) the box plot and TF of GMM sequences of fourth subject during two SCTs; (e) the box plot and TF of GMM sequences of fifth subject during two SCTs; (f) the box plot and TF of GMM sequences of sixth subject during two SCTs; (g) the box plot and TF of GMM sequences of seventh subject during two SCTs; and (h) the box plot and TF of GMM sequences of eighth subject during two SCTs

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Fig. 6

The box plot and histogram of GMM clusters of global model before (a) and after (b) fatigue protocol: (a) global model before fatigue protocol, (a1) the box plot of GMM sequences of global model during first SCT, (a2) the histogram of clusters of global model during first SCT and (b) global model after fatigue protocol, (b1) the boxplot of GMM sequences of global model during second SCT, (b2) the histogram of clusters of global model during second SCT

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Fig. 7

The TFs of GMM sequences of global model before and after fatigue protocol

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Fig. 8

Correlation between the relative decline from SCT 1 and SCT 2 for vertical work (%) and TF (%) (r2 = 0.74, P < 0.05) as a result of the fatigue protocol (repeat bout 30 s Wingate)

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