机器人的严密性:多发性硬化症中Kinarm端点机器人视觉引导到达测试的有效性。

IF 1.9 Q2 REHABILITATION
Nick W Bray, Syed Z Raza, Joselyn Romero Avila, Caitlin J Newell, Michelle Ploughman
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引用次数: 0

摘要

目的:确定机器人指标是否:(1)与九孔钉测试(9HPT)相关;收敛效度好);(2)区分那些自我报告的“有些手问题”和“没有手问题”(良好的标准效度)。设计:横断面验证分析。环境:医院内的康复研究实验室。参与者:多发性硬化症患者自我报告“一些”(n=21;平均年龄:52.52±10.69 y;女性,n = 16;病程(18.81±10.38 y) vs“无”(n=21;年龄:51.24±12.73 y;女性,n = 14;病程,17.71±10.16 y)手部问题。主要结果测量:我们使用标准9HPT和机器人测试评估了手功能。机器人结果包括总体任务得分、2项运动规划(即反应时间和初始方向角)和2项运动纠正(即运动时间和路径长度比)时空值。我们通过多发性硬化症影响量表29来确定报告“有些”和“没有”手部问题的参与者。我们使用Mann-Whitney U检验和Spearman秩序相关分析非参数数据。结果:报告“某些手问题”的人包括更多的右利手个体(P=.038);除此之外,两组的特征相似。视觉引导到达任务得分和动作计划而非动作纠正时空值与优势项的9HPT均呈中等相关性(反应时间:r=0.489, P=.001;初始方向角:r=0.429, P= 0.005)和非优势侧(反应时间:r=0.521, Pr=0.321, P= 0.038)。此外,两组之间的反应时间有差异,但9HPT或任何其他机器人结果没有差异(P= 0.036);那些报告“没有手部问题”的人移动得更快(即,主侧:0.2810 [0.2605-0.3215]vs 0.3400 [0.2735-0.3725] s)。结论:机器人测试指标在多发性硬化症中显示出适度的标准和收敛效度,反应时间是最引人注目的。在任务得分之外,时空机器人测量可能有助于识别与多发性硬化症相关的微妙手部问题。运动规划时空值似乎比运动纠正更有意义,并且可以证明作为未来干预策略的目标是富有成效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robotic Rigor: Validity of the Kinarm End-Point Robot Visually Guided Reaching Test in Multiple Sclerosis.

Objective: To determine whether robotic metrics: (1) correlate with the Nine-Hole Peg Test (9HPT; good convergent validity); and (2) differentiate between those self-reporting "some hand problems" versus "no hand problems" (good criterion validity).

Design: Cross-sectional validation analyses.

Setting: Rehabilitation research laboratory located within a hospital.

Participants: People with multiple sclerosis self-reporting "some" (n=21; mean age, 52.52±10.69 y; females, n=16; disease duration, 18.81±10.38 y) versus "no" (n=21; age, 51.24±12.73 y; females, n=14; disease duration, 17.71±10.16 y) hand problems.

Main outcome measures: We assessed hand function using the criterion standard 9HPT and robotic testing. Robotic outcomes included an overall task score, as well as 2 movement planning (ie, reaction time and initial direction angle) and 2 movement correction (ie, movement time and path length ratio) spatiotemporal values. We identified participants reporting "some" versus "no" hand problems via the Multiple Sclerosis Impact Scale-29. We analyzed our nonparametric data using a Mann-Whitney U test and Spearman rank-order correlation.

Results: Those reporting "some hand problems" included more right-handed individuals (P=.038); otherwise, the 2 groups were characteristically similar. Visually guided reaching task score and movement planning but not movement correction spatiotemporal values demonstrated moderate correlations with 9HPT for both the dominant (reaction time: r=0.489, P=.001; initial direction angle: r=0.429, P=.005) and nondominant (reaction time: r=0.521, P<.001; initial direction angle: r=0.321, P=.038) side. Further, reaction time, but not 9HPT or any other robotic outcome, differentiated between the 2 groups (P=.036); those reporting "no hand problems" moved faster (ie, dominant side: 0.2810 [0.2605-0.3215] vs 0.3400 [0.2735-0.3725] s).

Conclusions: Robotic test metrics demonstrated modest criterion and convergent validity in multiple sclerosis, with reaction time being the most compelling. When looking beyond the task score, spatiotemporal robotic measures may help discern subtle multiple sclerosis-related hand problems. Movement planning spatiotemporal values appear more meaningful than movement correction and could prove fruitful as the target for future intervention strategies.

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