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一种评估拇指本体感觉的新型机器人技术可预测中风后的手部功能。

A Novel Robotic Technique for Evaluating Thumb Proprioception Predicts Hand Function After Stroke.

作者信息

Garcia-Fernandez Luis, Farrens Andria, Rojas Raymond, Chan Vicky, Wolbrecht Eric, Perry Joel C, Reinkensmeyer David J

出版信息

IEEE Int Conf Rehabil Robot. 2025 May;2025:761-766. doi: 10.1109/ICORR66766.2025.11063148.

Abstract

The thumb has been called a "hallmark of humanity", and yet, in stroke rehabilitation, there are few studies that have examined thumb function and even fewer that have focused specifically on thumb sensory function. Here we describe a novel robotic technique to assess thumb proprioception and apply it to quantify the relationship between thumb proprioception and hand function after stroke. Based on a video game, "SomatoCircleJump" challenges participants to "jump" to radial targets presented on a screen as their thumb rotates around a circle, driven by a robot. Proprioceptive ability is quantified by radial jump error. We evaluated 35 individuals in the chronic phase post-stroke as part of a randomized controlled trial of robotic finger training. Compared to an agematched control group, people with stroke had significantly increased jump error ($\mathrm{p}<\text{0. 0 0 1}$). Thumb proprioception ability predicted hand function, as measured by the Box and Block Test score ($\rho=-0.44, \mathrm{p}=0.01$) and the Nine-Hole Peg Test time ($\rho= 0.49, \mathrm{p}=0.006$). Jump error was also correlated with an independent robotic measure of finger proprioception ($\rho=0.54, \mathrm{p}=0.003$). These results validate a novel robotic method to quantify thumb proprioception and indicate thumb proprioception deficits are common after stroke, co-occur with finger proprioception deficits, and relate to functional hand ability.

摘要

拇指被称为“人类的标志”,然而,在中风康复领域,很少有研究关注拇指功能,专门针对拇指感觉功能的研究更是少之又少。在此,我们描述一种评估拇指本体感觉的新型机器人技术,并将其应用于量化中风后拇指本体感觉与手部功能之间的关系。基于一款电子游戏,“体感圈跳”要求参与者在机器人驱动下,当拇指绕圈旋转时,“跳”向屏幕上呈现的桡侧目标。本体感觉能力通过桡侧跳跃误差来量化。作为机器人手指训练随机对照试验的一部分,我们评估了35名中风后慢性期患者。与年龄匹配的对照组相比,中风患者的跳跃误差显著增加(p<0.001)。拇指本体感觉能力可预测手部功能,通过箱块测试得分(ρ=-0.44,p=0.01)和九孔插板测试时间(ρ=0.49,p=0.006)来衡量。跳跃误差还与手指本体感觉的独立机器人测量值相关(ρ=0.54,p=0.003)。这些结果验证了一种量化拇指本体感觉的新型机器人方法,并表明中风后拇指本体感觉缺陷很常见,与手指本体感觉缺陷同时出现,且与手部功能能力相关。

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