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4D 运动捕捉系统与惯性测量单元系统在步态时空参数和关节运动学测量中的对比实验

Experimental Comparison between 4D Stereophotogrammetry and Inertial Measurement Unit Systems for Gait Spatiotemporal Parameters and Joint Kinematics.

机构信息

Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy.

4D4ALL Lab, Department of Rehabilitation Sciences and Physiotherapy, Center for Health and Technology (CHaT), Faculty of Medicine and Health Sciences, MOVANT, University of Antwerp, 2000 Antwerpen, Belgium.

出版信息

Sensors (Basel). 2024 Jul 18;24(14):4669. doi: 10.3390/s24144669.

DOI:10.3390/s24144669
PMID:39066067
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11280879/
Abstract

(1) Background: Traditional gait assessment methods have limitations like time-consuming procedures, the requirement of skilled personnel, soft tissue artifacts, and high costs. Various 3D time scanning techniques are emerging to overcome these issues. This study compares a 3D temporal scanning system (Move4D) with an inertial motion capture system (Xsens) to evaluate their reliability and accuracy in assessing gait spatiotemporal parameters and joint kinematics. (2) Methods: This study included 13 healthy people and one hemiplegic patient, and it examined stance time, swing time, cycle time, and stride length. Statistical analysis included paired samples -test, Bland-Altman plot, and the intraclass correlation coefficient (ICC). (3) Results: A high degree of agreement and no significant difference ( > 0.05) between the two measurement systems have been found for stance time, swing time, and cycle time. Evaluation of stride length shows a significant difference ( < 0.05) between Xsens and Move4D. The highest root-mean-square error (RMSE) was found in hip flexion/extension (RMSE = 10.99°); (4) Conclusions: The present work demonstrated that the system Move4D can estimate gait spatiotemporal parameters (gait phases duration and cycle time) and joint angles with reliability and accuracy comparable to Xsens. This study allows further innovative research using 4D (3D over time) scanning for quantitative gait assessment in clinical practice.

摘要

(1)背景:传统的步态评估方法存在耗时、需要专业人员、软组织伪影和成本高等局限性。各种 3D 时间扫描技术正在涌现,以克服这些问题。本研究比较了一种 3D 时间扫描系统(Move4D)和惯性运动捕捉系统(Xsens),以评估它们在评估步态时空参数和关节运动学方面的可靠性和准确性。(2)方法:本研究包括 13 名健康人和 1 名偏瘫患者,评估了站立时间、摆动时间、周期时间和步长。统计分析包括配对样本 t 检验、Bland-Altman 图和组内相关系数(ICC)。(3)结果:发现两种测量系统在站立时间、摆动时间和周期时间方面具有高度一致性,且无显著差异(>0.05)。评估步长时,Xsens 和 Move4D 之间存在显著差异(<0.05)。髋关节屈伸的均方根误差(RMSE)最高(RMSE=10.99°);(4)结论:本研究表明,Move4D 系统可以可靠且准确地估计步态时空参数(步态阶段持续时间和周期时间)和关节角度,与 Xsens 相当。本研究允许进一步使用 4D(3D 随时间变化)扫描进行创新研究,以在临床实践中进行定量步态评估。

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3
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Int J Obes (Lond). 2025 Apr;49(4):541-553. doi: 10.1038/s41366-024-01659-4. Epub 2024 Nov 19.
基于音乐的治疗-使用可穿戴设备的节奏听觉刺激(RAS)对神经科患者康复的影响:系统评价。
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