Tulimieri Duncan T, Kim GilHwan, Hoh Joanna E, Sergi Fabrizio, Semrau Jennifer A
Department of Kinesiology and Applied Physiology, University of Delaware, Tower at STAR, 100 Discovery Blvd, Rm 234, Newark, DE, 19713, USA.
Department of Mechanical Engineering, University of Delaware, Newark, USA.
J Neuroeng Rehabil. 2025 Jun 7;22(1):130. doi: 10.1186/s12984-025-01660-6.
Proprioceptive impairments of the upper limb are common after stroke. These impairments are not typically addressed during assessment or rehabilitation. Currently, most robotic paradigms for training of the upper limb have focused solely on improving motor function or have targeted proprioception in individuals with combined use of visual feedback. Our goal was to design a training paradigm that directly targets proprioception of the upper limb, while minimizing reliance on other sensory information to improve sensorimotor function after stroke.
In this pilot study, 5 individuals with stroke and 5 age-matched controls were tested on a single-day proprioceptive training paradigm. Here, participants used a joystick with their less-affected arm to send commands to a KINARM exoskeleton that would passively move their more-affected arm. To complete the passive reaching task, participants relied only on proprioceptive feedback from the more-affected arm and were only given knowledge of results information after each trial. Sensorimotor function of the upper limb was measured pre- and post-training via robotic measures of motor function [Visually Guided Reaching (VGR)] and position sense [Arm Position Matching (APM)]. Sensorimotor function was quantified as a Task Score, which incorporated multiple task-relevant parameters for both VGR and APM. Changes in sensorimotor performance due to training were calculated as the pre- to post-training difference for VGR and APM within the control and stroke groups.
We found significant improvements from pre-training to post-training for VGR in individuals with stroke (p < 0.001, CLES = 100) that were not observed in control participants (p = 0.87, CLES = 80). We observed significant changes from pre- to post-training in both VGR (Posture Speed, Reaction Time, Initial Direction Angle, Min-Max Speed Difference, and Movement Time) and APM (Contraction/Expansion Ratio and Shift) parameters.
Our novel proprioceptive training paradigm is one of the first to implement a self-guided sensory training protocol. We observed improvements in motor function and proprioception for individuals with stroke. This pilot study demonstrates the feasibility of self-guided proprioceptive training to improve motor and sensory function in individuals with stroke. Future studies aim to examine multi-day training to examine longer-term impacts on upper limb sensorimotor function.
中风后上肢本体感觉障碍很常见。在评估或康复过程中,这些障碍通常未得到处理。目前,大多数用于上肢训练的机器人模式仅专注于改善运动功能,或者在结合使用视觉反馈的个体中针对本体感觉。我们的目标是设计一种训练模式,直接针对上肢的本体感觉,同时尽量减少对其他感觉信息的依赖,以改善中风后的感觉运动功能。
在这项初步研究中,对5名中风患者和5名年龄匹配的对照者进行了单日本体感觉训练模式测试。在此,参与者用受影响较小的手臂使用操纵杆向KINARM外骨骼发送命令,该外骨骼会被动移动他们受影响较大的手臂。为了完成被动伸手任务,参与者仅依靠受影响较大手臂的本体感觉反馈,并且在每次试验后仅获得结果信息。在训练前后,通过运动功能的机器人测量[视觉引导伸手(VGR)]和位置感觉[手臂位置匹配(APM)]来测量上肢的感觉运动功能。感觉运动功能被量化为任务得分,该得分纳入了VGR和APM的多个与任务相关的参数。训练引起的感觉运动表现变化计算为对照组和中风组中VGR和APM训练前到训练后的差异。
我们发现中风患者从训练前到训练后VGR有显著改善(p < 0.001,CLES = 100),而对照参与者未观察到这种改善(p = 0.87,CLES = 80)。我们观察到VGR(姿势速度、反应时间、初始方向角、最小-最大速度差和运动时间)和APM(收缩/扩张比和偏移)参数从训练前到训练后都有显著变化。
我们新颖的本体感觉训练模式是最早实施自我引导感觉训练方案的模式之一。我们观察到中风患者的运动功能和本体感觉有所改善。这项初步研究证明了自我引导本体感觉训练改善中风患者运动和感觉功能的可行性。未来的研究旨在检查多日训练,以研究对上肢感觉运动功能的长期影响。