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使用无标记运动捕捉和肌肉骨模型:对关节动力学的评估
Simon Auer1, Franz Süß1,2, Sebastian Dendorfer1,2
1Laboratory for Biomechanics, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.
概括
基于视频的动作捕捉 (VMC) 显示出分析下半身和肩膀动态的前景,为基于标记器的动作捕捉 (MMC) 提供了可行的替代方案. 然而,手腕和肘部运动的准确性需要进一步的细化.
科学领域:
- 生物力学 生物力学
- 运动捕捉技术的技术.
- 肌肉骨系统建模
背景情况:
- 基于标记器的运动捕捉 (MMC) 和基于视频的运动捕捉 (VMC) 系统进行动力分析.
- 评估VMC作为生物力学研究中可访问的替代品.
研究的目的:
- 使用肌肉骨模型评估VMC准确度,以计算关节角度.
- 量化MMC和VMC系统之间的动力学偏差.
主要方法:
- 收集了来自18名健康人群的动力学数据,他们使用MMC和VMC进行了分离运动.
- 使用AnyBody建模系统进行关节角度计算.
- 计算平均绝对误差 (MAE) 来确定系统偏差.
主要成果:
- 在肩膀 (MAE 4.8°),部 (MAE 6.8°) 和膝盖 (MAE 3.5°) 关节角度上,VMC与MMC显示出良好的一致性.
- 在手 (13.7°),肘 (27.7°),头部和胸部运动中观察到更高的MAE值,表明跟踪挑战.
- 对下半身和肩膀动力学的有希望的准确性被注意到.
结论:
- VMC是下半身和肩膀运动分析的可行工具,但手腕和骨盆跟踪需要改进.
- 这些发现支持进一步研究将VMC与肌肉骨模型相结合,以进行增强的生物力学分析.
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