Quantitative evaluation of subjective posture recognition by physiotherapists using a 3D motion capture
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Updated: Dec 10, 2025

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography
Published on: January 12, 2024
Masumi Shingai1, Ren Niijima2, Yuto Kobayashi1
1Faculty of Rehabilitation, Gunma University of Health and Welfare: K´BIX-Genki21-Maebashi-6F, 2-12-1 Honmachi, Maebashi, Gunma 371-0023, Japan.
Abstract:
[Purpose] This study evaluated subjective posture recognition by physiotherapists with expertise in posture, examined the quantification of posture using a three-dimensional (3D) motion capture, and described posture-based characteristics. [Participants and Methods] We photographed good, normal, and bad postures in 12 participants using an infrared camera, and the resultant data were analyzed. [Results] We observed the largest displacement from a good to a bad posture in the tenth thoracic vertebra on the X-axis in the anterior-posterior direction in comparison with other index points. Further, we observed considerable differences between good and bad postures compared with other index points. Moreover, we noted significant differences between the amount of displacement between good to a normal posture and from a good to a bad posture. The vertical displacement of the Z-axis was smaller than other index points. [Conclusion] Th10 captured features from the three postures. The X-axis was displaced most between good and bad postures. Further, the amount of displacement on the Z-axis was less between good and bad posture, rendering it difficult to capture features. Therefore, the findings reported herein can be used to compare the front and rear directions of the X-axis for capturing postural changes.
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