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Phys. Ther. Korea 2022; 29(4): 262-268
Published online November 20, 2022
https://doi.org/10.12674/ptk.2022.29.4.262
© Korean Research Society of Physical Therapy
Correlation Between Knee Muscle Strength and Maximal Cycling Speed Measured Using 3D Depth Camera in Virtual Reality Environment
Ye Jin Kim1 
, PT, BPT, Hye-seon Jeon2,3 , PT, PhD, Joo-hee Park2 , PT, PhD, Gyeong-Ah Moon1 , PT, BPT, Yixin Wang1 , PT, BPT
1Department of Physical Therapy, The Graduate School, Yonsei University, 2Department of Physical Therapy, College of Health Science, Yonsei University, 3Department of Ergonomic Therapy, The Graduate School of Health and Environment, Yonsei University, Wonju, Korea
Correspondence to: Hye-seon Jeon
E-mail: hyeseonj@yonsei.ac.kr
https://orcid.org/0000-0003-3986-2030
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: Virtual reality (VR) programs based on motion capture camera are the most convenient and cost-effective approaches for remote rehabilitation. Assessment of physical function is critical for providing optimal VR rehabilitation training; however, direct muscle strength measurement using camera-based kinematic data is impracticable. Therefore, it is necessary to develop a method to indirectly estimate the muscle strength of users from the value obtained using a motion capture camera. Objects: The purpose of this study was to determine whether the pedaling speed converted using the VR engine from the captured foot position data in the VR environment can be used as an indirect way to evaluate knee muscle strength, and to investigate the validity and reliability of a camera-based VR program.
Methods: Thirty healthy adults were included in this study. Each subject performed a 15-second maximum pedaling test in the VR and built-in speedometer modes. In the VR speedometer mode, a motion capture camera was used to detect the position of the ankle joints and automatically calculate the pedaling speed. An isokinetic dynamometer was used to assess the isometric and isokinetic peak torques of knee flexion and extension.
Results: The pedaling speeds in VR and built-in speedometer modes revealed a significantly high positive correlation (r = 0.922). In addition, the intra-rater reliability of the pedaling speed in the VR speedometer mode was good (ICC [intraclass correlation coefficient] = 0.685). The results of the Pearson correlation analysis revealed a significant moderate positive correlation between the pedaling speed of the VR speedometer and the peak torque of knee isokinetic flexion (r = 0.639) and extension (r = 0.598).
Conclusion: This study suggests the potential benefits of measuring the maximum pedaling speed using 3D depth camera in a VR environment as an indirect assessment of muscle strength. However, technological improvements must be followed to obtain more accurate estimation of muscle strength from the VR cycling test.
Keywords: Bicycling, Muscle strength, Rehabilitation, Virtual reality
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Original Article
Phys. Ther. Korea 2022; 29(4): 262-268
Published online November 20, 2022 https://doi.org/10.12674/ptk.2022.29.4.262
Copyright © Korean Research Society of Physical Therapy.
Correlation Between Knee Muscle Strength and Maximal Cycling Speed Measured Using 3D Depth Camera in Virtual Reality Environment
Ye Jin Kim1 , PT, BPT, Hye-seon Jeon2,3 , PT, PhD, Joo-hee Park2 , PT, PhD, Gyeong-Ah Moon1 , PT, BPT, Yixin Wang1 , PT, BPT
1Department of Physical Therapy, The Graduate School, Yonsei University, 2Department of Physical Therapy, College of Health Science, Yonsei University, 3Department of Ergonomic Therapy, The Graduate School of Health and Environment, Yonsei University, Wonju, Korea
Correspondence to:Hye-seon Jeon
E-mail: hyeseonj@yonsei.ac.kr
https://orcid.org/0000-0003-3986-2030
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Virtual reality (VR) programs based on motion capture camera are the most convenient and cost-effective approaches for remote rehabilitation. Assessment of physical function is critical for providing optimal VR rehabilitation training; however, direct muscle strength measurement using camera-based kinematic data is impracticable. Therefore, it is necessary to develop a method to indirectly estimate the muscle strength of users from the value obtained using a motion capture camera. Objects: The purpose of this study was to determine whether the pedaling speed converted using the VR engine from the captured foot position data in the VR environment can be used as an indirect way to evaluate knee muscle strength, and to investigate the validity and reliability of a camera-based VR program.
Methods: Thirty healthy adults were included in this study. Each subject performed a 15-second maximum pedaling test in the VR and built-in speedometer modes. In the VR speedometer mode, a motion capture camera was used to detect the position of the ankle joints and automatically calculate the pedaling speed. An isokinetic dynamometer was used to assess the isometric and isokinetic peak torques of knee flexion and extension.
Results: The pedaling speeds in VR and built-in speedometer modes revealed a significantly high positive correlation (r = 0.922). In addition, the intra-rater reliability of the pedaling speed in the VR speedometer mode was good (ICC [intraclass correlation coefficient] = 0.685). The results of the Pearson correlation analysis revealed a significant moderate positive correlation between the pedaling speed of the VR speedometer and the peak torque of knee isokinetic flexion (r = 0.639) and extension (r = 0.598).
Conclusion: This study suggests the potential benefits of measuring the maximum pedaling speed using 3D depth camera in a VR environment as an indirect assessment of muscle strength. However, technological improvements must be followed to obtain more accurate estimation of muscle strength from the VR cycling test.
Keywords: Bicycling, Muscle strength, Rehabilitation, Virtual reality
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Table 1 . General characteristics of the participants (N = 30).
Variable Male (n = 18) Female (n = 12) Age (y) 26.61 ± 2.34 25.75 ± 3.61 Height (cm) 174.61 ± 6.91 160.0 ± 3.67 Weight (kg) 73.57 ± 8.62 52.64 ± 3.92 Body mass index (kg/m2) 24.09 ± 2.07 20.59 ± 1.71 Values are presented as mean ± standard deviation..
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Table 2 . Pedaling speed in maximum cycling test.
VR
speedometerBuilt-in
speedometerValidity (r) Pedaling speed (rpm)a 6.75 ± 1.22 12.59 ± 2.23 0.922 Values are presented as mean ± standard deviation. VR, virtual reality..
aAverage pedaling speed during 15 seconds maximum cycling test..
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Table 3 . Intra-rater reliability of pedaling speed.
ICC (95% CI) p-value VR speedometer 0.685 (0.511–0.821) < 0.001 Built-in speedometer 0.935 (0.884–0.958) < 0.001 ICC, intraclass correlation coefficient; CI, confidence interval; VR, virtual reality..
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Table 4 . Knee flexion and extension peak torque measured using Biodex (Shirley) dynamometer.
Isometric (Nm) Isokinetic (Nm) Flexion Extension Flexion Extension VR speedometer 0.419 (0.021*) 0.478 (0.008**) 0.639 (0.000***) 0.598 (0.000***) Built-in speedometer 0.444 (0.014*) 0.424 (0.019*) 0.652 (0.000***) 0.558 (0.001**) Values are presented as Pearson correlation coefficient [r] (p-value). *p < 0.05, **p < 0.01, ***p < 0.001..