Internet of Things (IoT) Enables Robot-Assisted Therapy as a Home Program for Training Upper Limb Functions in Chronic Stroke: A Randomized Control Crossover Study

改良阿什沃思量表 手腕 物理医学与康复 交叉研究 冲程(发动机) 慢性中风 医学 物理疗法 康复 随机对照试验 上肢 日常生活活动 运动范围 定时启动测试 外科 病理 替代医学 平衡(能力) 工程类 机械工程 安慰剂
作者
Li‐Chieh Kuo,Kang-Chin Yang,Yu‐Ching Lin,Yu‐Chen Lin,Chien-Hsien Yeh,Fong‐Chin Su,Hsiu‐Yun Hsu
出处
期刊:Archives of Physical Medicine and Rehabilitation [Elsevier BV]
卷期号:104 (3): 363-371 被引量:6
标识
DOI:10.1016/j.apmr.2022.08.976
摘要

Objective To compare the effects of using an Internet of things (IoT)-assisted tenodesis-induced-grip exoskeleton robot (TIGER) and task-specific motor training (TSMT) as home programs for the upper-limb (UL) functions of patients with chronic stroke to overturn conventional treatment modes for stroke rehabilitation. Design A randomized 2-period crossover study. Setting A university hospital. Participants Eighteen chronic stroke patients were recruited and randomized to receive either the IoT-assisted TIGER first or TSMT first at the beginning of the experiment (N=18). Intervention In addition to the standard hospital-based therapy, participants were allocated to receive a 30-minute home-based, self-administered program of either IoT-assisted TIGER first or TSMT first twice daily for 4 weeks, with the order of both treatments reversed after a 12-week washout period. The exercise mode of the TIGER training included continuous passive motion and the functional mode of gripping pegs. The TSMT involved various movement components of the wrist and hand. Main Outcome Measures The outcome measures included the box and block test (BBT), the Fugl-Meyer assessment for upper extremity (FMA-UE), the motor activity log, the Semmes-Weinstein Monofilament test, the range of motion (ROM) of the wrist joint, and the modified Ashworth scale. Results Significant treatment-by-time interaction effects emerged in the results for the BBT (F(1.31)=5.212 and P=.022), the FMA-UE (F(1.31)=6.807 and P=.042), and the ROM of the wrist extension (F(1.31)=8.618 and P=.009). The participants who trained at home with the IoT-assisted TIGER showed more improvement of their UL functions. Conclusions The IoT-assisted TIGER training has the potential for restoring the UL functions of stroke patients.
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