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基于无标记运动捕捉和肌肉骨骼模型的关节运动学评估。

Using markerless motion capture and musculoskeletal models: An evaluation of joint kinematics.

机构信息

Laboratory for Biomechanics, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.

Regensburg Center of Biomedical Engineering, Ostbayerische Technische Hochschule and University Regensburg, Germany.

出版信息

Technol Health Care. 2024;32(5):3433-3442. doi: 10.3233/THC-240202.

Abstract

BACKGROUND

This study presents a comprehensive comparison between a marker-based motion capture system (MMC) and a video-based motion capture system (VMC) in the context of kinematic analysis using musculoskeletal models.

OBJECTIVE

Focusing on joint angles, the study aimed to evaluate the accuracy of VMC as a viable alternative for biomechanical research.

METHODS

Eighteen healthy subjects performed isolated movements with 17 joint degrees of freedom, and their kinematic data were collected using both an MMC and a VMC setup. The kinematic data were entered into the AnyBody Modelling System, which enables the calculation of joint angles. The mean absolute error (MAE) was calculated to quantify the deviations between the two systems.

RESULTS

The results showed good agreement between VMC and MMC at several joint angles. In particular, the shoulder, hip and knee joints showed small deviations in kinematics with MAE values of 4.8∘, 6.8∘ and 3.5∘, respectively. However, the study revealed problems in tracking hand and elbow movements, resulting in higher MAE values of 13.7∘ and 27.7∘. Deviations were also higher for head and thoracic movements.

CONCLUSION

Overall, VMC showed promising results for lower body and shoulder kinematics. However, the tracking of the wrist and pelvis still needs to be refined. The research results provide a basis for further investigations that promote the fusion of VMC and musculoskeletal models.

摘要

背景

本研究在使用肌肉骨骼模型进行运动学分析的背景下,对基于标记的运动捕捉系统(MMC)和基于视频的运动捕捉系统(VMC)进行了全面比较。

目的

本研究聚焦于关节角度,旨在评估 VMC 作为生物力学研究可行替代方案的准确性。

方法

18 名健康受试者进行了 17 个自由度的孤立运动,其运动学数据分别使用 MMC 和 VMC 采集。运动学数据被输入到 AnyBody 建模系统中,该系统可以计算关节角度。平均绝对误差(MAE)被用来量化两个系统之间的偏差。

结果

结果表明,VMC 和 MMC 在几个关节角度上具有良好的一致性。特别是在肩部、臀部和膝关节,运动学的偏差较小,MAE 值分别为 4.8∘、6.8∘和 3.5∘。然而,研究发现对手部和肘部运动的跟踪存在问题,导致 MAE 值分别高达 13.7∘和 27.7∘。头部和胸部运动的偏差也较高。

结论

总体而言,VMC 在手和骨盆的跟踪方面仍需进一步改进,但其对于下肢和肩部的运动学表现出了较好的效果。研究结果为进一步推动 VMC 和肌肉骨骼模型的融合提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8849/11492134/d0489826973a/thc-32-thc240202-g001.jpg

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