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arXiv 2610.05552cs.CV

单目无标记生物力学用于脊髓损伤临床可解释步态评估

Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injury

Shreyasvi Natraj, Mathieu Ruepp, Yanke Li, Robert Riener, Inge Eriks-Hoogland, Diego Paez-Granados

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中文总结 AI 辅助

本研究提出单目无标记视频结合OpenSim模型,在脊髓损伤患者中实现临床可解释的步态生物力学评估,并验证其与运动捕捉和测力台的一致性,为可扩展的临床评估提供新方法。

中文摘要 AI 辅助

三维步态分析指导脊髓损伤后的康复,但依赖于基于标记的运动捕捉和测力台,而很少有临床机构具备这些设备。单目无标记流程已在少数健康成人队列中建立,但尚未在神经科队列中验证。我们提出了SCAI SCI Gait数据集,包含239名患有脊髓损伤的成人个体,具有同步的视频、运动捕捉和测力台测量数据,我们将参数化人体网格拟合到单个矢状面视频,通过虚拟标记驱动按人体测量学缩放的OpenSim模型。无标记下肢运动学与运动捕捉测量表现出最先进的一致性(r = 0.68-0.90,p < 0.001,RMSE = 4.18-6.49度),且基于运动学的准确预测地面反作用力与测力台测量紧密匹配(r = 0.85-0.87,p < 0.001,RMSE = 2.13-2.19牛顿每千克)。此外,使用马尔可夫毯的条件依赖图分析显示,波形成分与功能独立性条件相关,而速度分层聚类揭示了以相似速度行走的个体中不同的机械策略。这些发现确立了单目视频作为一种可扩展的方法,用于对脊髓损伤患者进行临床有意义的生物力学评估和数据驱动的表型分析。Github:此https URL

英文摘要

Three-dimensional gait analysis guides rehabilitation after spinal cord injury but depends on marker-based motion capture and force plates, which few clinics have. Monocular markerless pipelines have been established in fewer healthy adult cohorts but not in neurological cohorts. We present the SCAI SCI Gait dataset, comprising 239 adult individuals with spinal cord injury with synchronized video, motion capture, and force-plate measurements, we fitted a parametric body mesh to a single sagittal-view video, driving an anthropometrically scaled OpenSim model via virtual markers. Markerless lower-body kinematics showed state-of-the-art agreement with motion-capture measurements (r = 0.68-0.90, p < 0.001, and RMSE = 4.18-6.49 degrees), and accurate kinematics-based predicted ground-reaction forces closely matched those measured by force plates (r = 0.85-0.87, p < 0.001, and RMSE = 2.13-2.19 Newton per kg). Furthermore, conditional-dependence graph analysis with Markov blankets revealed that waveform components were conditionally associated with functional independence, and speed-stratified clustering revealed distinct mechanical strategies among individuals walking at similar speeds. These findings establish the use of monocular video as a scalable approach for clinically meaningful biomechanical assessment and data-driven phenotyping in patients with spinal cord injury. Github: https://github.com/SCAI-Lab/SCAI-SCI-Gait-Dataset

发表机构

  • Swiss Paraplegic Research(瑞士截瘫研究中心)
  • University Hospital Balgrist(巴尔格里斯特大学医院)
  • Tohoku University(东北大学)
  • University of Lucerne(卢塞恩大学)
  • Swiss Paraplegic Centre(瑞士截瘫中心)
  • University of Tsukuba(筑波大学)

机构由 AI 辅助整理,请以论文原文为准。

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