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English(EN) Quantifying Rodda and Graham Gait Classification from 3D Makerless Kinematics derived from a Single-view Video in a Heterogeneous Pediatric Clinical Cohort

无标记步态分析系统可量化儿童运动障碍

研究人员开发了一种新颖的无标记步态分析系统,能够从单视角临床视频中量化步态偏差。该系统估算了Rodda和Graham的膝关节和踝关节z分数,与传统的3D仪器步态分析相比,准确度很高。该技术有望实现可扩展、客观的步态评估,尤其是在资源匮乏的临床环境中,并支持疾病进展和治疗反应的纵向追踪。 AI

影响 为儿童运动障碍提供更易于获得和更客观的步态评估,有望改善诊断和治疗监测。

排序理由 该集群包含一篇详细介绍新方法及其评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Lauhitya Reddy, Seth Donahue, Jeremy Bauer, Susan Sienko, Anita Bagley, Joseph Krzak, Maura Eveld, Karen Kruger, Ross Chafetz, Vedant Kulkarni, Hyeokhyen Kwon ·

    Quantifying Rodda and Graham Gait Classification from 3D Makerless Kinematics derived from a Single-view Video in a Heterogeneous Pediatric Clinical Cohort

    arXiv:2605.11314v2 Announce Type: replace Abstract: Cerebral Palsy (CP) is a neurological disorder of movement and the most common cause of lifelong physical disability in childhood. Approximately 75% of children with CP are ambulatory, and accurate gait assessment is central to …