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重度中风后手臂运动训练的自动化:在减重环境下进行的具有定量反馈的功能锻炼。

Automating arm movement training following severe stroke: functional exercises with quantitative feedback in a gravity-reduced environment.

作者信息

Sanchez Robert J, Liu Jiayin, Rao Sandhya, Shah Punit, Smith Robert, Rahman Tariq, Cramer Steven C, Bobrow James E, Reinkensmeyer David J

机构信息

Department of Mechanical and Aerospace Engienering, University of California, Irvine, CA 92697-3975, USA.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2006 Sep;14(3):378-89. doi: 10.1109/TNSRE.2006.881553.

DOI:10.1109/TNSRE.2006.881553
PMID:17009498
Abstract

An important goal in rehabilitation engineering is to develop technology that allows individuals with severe motor impairment to practice arm movement without continuous supervision from a rehabilitation therapist. This paper describes the development of such a system, called Therapy WREX or ("T-WREX"). The system consists of an orthosis that assists in arm movement across a large workspace, a grip sensor that detects hand grip pressure, and software that simulates functional activities. The arm orthosis is an instrumented, adult-sized version of the Wilmington Robotic Exoskeleton (WREX), which is a five degrees-of-freedom mechanism that passively counterbalances the weight of the arm using elastic bands. After providing a detailed design description of T-WREX, this paper describes two pilot studies of the system's capabilities. The first study demonstrated that individuals with chronic stroke whose arm function is compromised in a normal gravity environment can perform reaching and drawing movements while using T-WREX. The second study demonstrated that exercising the affected arm of five people with chronic stroke with T-WREX over an eight week period improved unassisted movement ability (mean change in Fugl-Meyer score was 5 points +/- 2 SD; mean change in range of motion of reaching was 10%, p < 0.001). These results demonstrate the feasibility of automating upper-extremity rehabilitation therapy for people with severe stroke using passive gravity assistance, a grip sensor, and simple virtual reality software.

摘要

康复工程的一个重要目标是开发一种技术,使严重运动障碍患者能够在无需康复治疗师持续监督的情况下练习手臂运动。本文描述了这样一种系统的开发,即治疗性威尔明顿机器人外骨骼系统(Therapy WREX 或 “T-WREX”)。该系统由一个在大工作空间内辅助手臂运动的矫形器、一个检测手握压力的握力传感器以及模拟功能活动的软件组成。手臂矫形器是威尔明顿机器人外骨骼(WREX)的成人尺寸的仪器化版本,它是一种五自由度机构,利用弹性带被动平衡手臂重量。在详细描述了 T-WREX 的设计之后,本文介绍了两项关于该系统功能的初步研究。第一项研究表明,在正常重力环境下手臂功能受损的慢性中风患者在使用 T-WREX 时能够进行够物和绘图动作。第二项研究表明,对五名慢性中风患者的患侧手臂使用 T-WREX 进行为期八周的锻炼,可提高其自主运动能力(Fugl-Meyer 评分的平均变化为 5 分 +/- 2 标准差;够物动作的运动范围平均变化为 10%,p < 0.001)。这些结果证明了利用被动重力辅助、握力传感器和简单虚拟现实软件对严重中风患者进行上肢康复治疗自动化的可行性。

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