Suppr超能文献

微软Kinect系统在评估站立和跑步机行走时的代偿性步行动为中的有效性。

Validity of the microsoft kinect system in assessment of compensatory stepping behavior during standing and treadmill walking.

作者信息

Shani Guy, Shapiro Amir, Oded Goldstein, Dima Kagan, Melzer Itshak

机构信息

Department of Software and Information Systems Engineering, Faculty of Engineering Sciences, Ben-Gurion University, Beer-Sheva, Israel.

Department of Mechanical Engineering, Faculty of Engineering Sciences, Ben-Gurion University, Beer-Sheva, Israel.

出版信息

Eur Rev Aging Phys Act. 2017 Mar 7;14:4. doi: 10.1186/s11556-017-0172-8. eCollection 2017.

Abstract

BACKGROUND

Rapid compensatory stepping plays an important role in preventing falls when balance is lost; however, these responses cannot be accurately quantified in the clinic. The Microsoft Kinect™ system provides real-time anatomical landmark position data in three dimensions (3D), which may bridge this gap.

METHODS

Compensatory stepping reactions were evoked in 8 young adults by a sudden platform horizontal motion on which the subject stood or walked on a treadmill. The movements were recorded with both a 3D-APAS motion capture and Microsoft Kinect™ systems. The outcome measures consisted of compensatory step times (milliseconds) and length (centimeters). The average values of two standing and walking trials for Microsoft Kinect™ and the 3D-APAS systems were compared using -test, Pearson's correlation, Altman-bland plots, and the average difference of root mean square error (RMSE) of joint position.

RESULTS

The Microsoft Kinect™ had high correlations for the compensatory step times ( = 0.75-0.78,  = 0.04) during standing and moderate correlations for walking ( = 0.53-0.63,  = 0.05). The step length, however had a very high correlations for both standing and walking ( > 0.97,  = 0.01). The RMSE showed acceptable differences during the perturbation trials with smallest relative error in anterior-posterior direction (2-3%) and the highest in the vertical direction (11-13%). No systematic bias were evident in the Bland and Altman graphs.

CONCLUSIONS

The Microsoft Kinect™ system provides comparable data to a video-based 3D motion analysis system when assessing step length and less accurate but still clinically acceptable for step times during balance recovery when balance is lost and fall is initiated.

摘要

背景

当失去平衡时,快速补偿性踏步在预防跌倒中起着重要作用;然而,这些反应在临床上无法准确量化。微软Kinect™系统可提供三维(3D)实时解剖标志点位置数据,这可能弥补这一差距。

方法

通过让8名年轻人站在或在跑步机上行走的平台突然水平移动,诱发其补偿性踏步反应。使用3D-APAS动作捕捉系统和微软Kinect™系统记录这些动作。结果测量包括补偿性踏步时间(毫秒)和步长(厘米)。使用t检验、Pearson相关性分析、Altman-Bland图以及关节位置均方根误差(RMSE)的平均差异,比较微软Kinect™系统和3D-APAS系统在两次站立和行走试验中的平均值。

结果

微软Kinect™系统在站立时对补偿性踏步时间具有高度相关性(r = 0.75 - 0.78,p = 0.04),在行走时具有中等相关性(r = 0.53 - 0.63,p = 0.05)。然而,步长在站立和行走时均具有非常高的相关性(r > 0.97,p = 0.01)。在扰动试验期间,RMSE显示出可接受的差异,前后方向相对误差最小(2 - 3%),垂直方向相对误差最大(11 - 13%)。Bland和Altman图中未明显显示出系统偏差。

结论

在评估步长时,微软Kinect™系统提供的数据与基于视频的3D运动分析系统相当;在平衡丧失和跌倒开始时的平衡恢复过程中,对于踏步时间,其数据准确性较低,但仍在临床可接受范围内。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e613/5339957/626c41488d4b/11556_2017_172_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验