Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill

Torvinen, Petra; Ruotsalainen, Keijo S.; Zhao, Shuang; Cronin, Neil; Ohtonen, Olli; Linnamo, Vesa

doi:10.3390/bioengineering11020136

Open AccessArticle

Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill

by

Petra Torvinen

^*

,

Keijo S. Ruotsalainen

,

Shuang Zhao

,

Neil Cronin

,

Olli Ohtonen

and

Vesa Linnamo

Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland

^*

Author to whom correspondence should be addressed.

Bioengineering 2024, 11(2), 136; https://doi.org/10.3390/bioengineering11020136

Submission received: 21 December 2023 / Revised: 23 January 2024 / Accepted: 26 January 2024 / Published: 29 January 2024

(This article belongs to the Special Issue Biomechanics-Based Motion Analysis, Volume II)

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Abstract

In this study, we developed a deep learning-based 3D markerless motion capture system for skate skiing on a treadmill and evaluated its accuracy against marker-based motion capture during G1 and G3 skating techniques. Participants performed roller skiing trials on a skiing treadmill. Trials were recorded with two synchronized video cameras (100 Hz). We then trained a custom model using DeepLabCut, and the skiing movements were analyzed using both DeepLabCut-based markerless motion capture and marker-based motion capture systems. We statistically compared joint centers and joint vector angles between the methods. The results demonstrated a high level of agreement for joint vector angles, with mean differences ranging from −2.47° to 3.69°. For joint center positions and toe placements, mean differences ranged from 24.0 to 40.8 mm. This level of accuracy suggests that our markerless approach could be useful as a skiing coaching tool. The method presents interesting opportunities for capturing and extracting value from large amounts of data without the need for markers attached to the skier and expensive cameras.

Keywords: kinematics; motion analysis; artificial intelligence; treadmill skiing; markerless motion capture

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MDPI and ACS Style

Torvinen, P.; Ruotsalainen, K.S.; Zhao, S.; Cronin, N.; Ohtonen, O.; Linnamo, V. Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill. Bioengineering 2024, 11, 136. https://doi.org/10.3390/bioengineering11020136

AMA Style

Torvinen P, Ruotsalainen KS, Zhao S, Cronin N, Ohtonen O, Linnamo V. Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill. Bioengineering. 2024; 11(2):136. https://doi.org/10.3390/bioengineering11020136

Chicago/Turabian Style

Torvinen, Petra, Keijo S. Ruotsalainen, Shuang Zhao, Neil Cronin, Olli Ohtonen, and Vesa Linnamo. 2024. "Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill" Bioengineering 11, no. 2: 136. https://doi.org/10.3390/bioengineering11020136

APA Style

Torvinen, P., Ruotsalainen, K. S., Zhao, S., Cronin, N., Ohtonen, O., & Linnamo, V. (2024). Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill. Bioengineering, 11(2), 136. https://doi.org/10.3390/bioengineering11020136

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Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill

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