Farrens Andria J, Reinsdorf Dylan, Garcia-Fernandez Luis, Rojas Raymond Diaz, Chan Vicky, Perry Joel, Wolbrecht Eric T, Reinkensmeyer David J
University of California, Irvine, United States.
University of Idaho, Moscow, United States.
J Neuroeng Rehabil. 2025 Jul 18;22(1):167. doi: 10.1186/s12984-025-01667-z.
Standard robotic therapy for upper extremity stroke rehabilitation provides physical assistance during video game-based training. While effective, it requires complex equipment, focuses on visuo-motor control, and yields variable results—raising the question: can more pragmatic or targeted movement training strategies be developed? To explore this, we pilot tested two novel robotic therapy modes. In the Virtual Assistance mode, game parameters are modulated to promote task completion without physical assistance – potentially useful when only sensors are available, although its acceptability for people with more severe motor impairment is unclear. In the Proprioceptive Training mode, participants play video games through a combination of visual and haptic cues. This approach aims to retrain proprioception but may also be too challenging for individuals with proprioceptive impairment to find it motivating. This study tested the feasibility of both variants across a range of motor and proprioceptive impairments, comparing them to training with Standard robotic therapy.
Chronic stroke participants ( = 46) were randomized to receive Standard, Virtual, or Proprioceptive Training. Participants used the FINGER robot to train in three sessions across one week, during which an adaptive algorithm titrated success to ~ 80%. Baseline proprioceptive and motor function were assessed prior to training, and motivation for training was assessed using the Intrinsic Motivation Inventory. Feasibility was evaluated by levels of gameplay success and motivation for training.
Participants of widely varying motor and proprioceptive ability achieved ~ 80% success for all three modes. However, Virtual Assistance resulted in significantly diminished motivation, due to lower perceived competence when participants were not provided with physical assistance. Participants with impaired proprioception rated Proprioceptive Training engaging, although it was more challenging for them and they required an increased level of assistance.
Both training paradigms were feasible for use with chronic stroke survivors and were able to achieve high gameplay success and motivation for training. However, physical assistance appeared to have an advantage over Virtual Assistance in raising training motivation. Proprioceptive Training required high levels of assistance, but was motivating even for people with poor proprioception.
The online version contains supplementary material available at 10.1186/s12984-025-01667-z.
用于上肢中风康复的标准机器人疗法在基于视频游戏的训练过程中提供物理辅助。虽然有效,但它需要复杂的设备,侧重于视觉运动控制,且效果不一——这就引发了一个问题:能否开发出更实用或更有针对性的运动训练策略?为了探索这一问题,我们对两种新型机器人疗法模式进行了初步测试。在虚拟辅助模式下,游戏参数会被调整以促进在无物理辅助的情况下完成任务——当只有传感器可用时可能会很有用,不过对于运动障碍更严重的人来说其可接受性尚不清楚。在本体感觉训练模式下,参与者通过视觉和触觉线索的组合来玩视频游戏。这种方法旨在重新训练本体感觉,但对于本体感觉受损的个体来说可能也具有挑战性,难以激发他们的积极性。本研究测试了这两种变体在一系列运动和本体感觉障碍中的可行性,并将它们与标准机器人疗法训练进行比较。
将慢性中风参与者(n = 46)随机分为接受标准训练、虚拟训练或本体感觉训练。参与者使用FINGER机器人在一周内进行三次训练,在此期间,一种自适应算法将成功率调整至约80%。在训练前评估基线本体感觉和运动功能,并使用内在动机量表评估训练动机。通过游戏玩法的成功率和训练动机水平来评估可行性。
所有三种模式下,运动和本体感觉能力差异很大的参与者都达到了约80%的成功率。然而,虚拟辅助导致动机显著降低,因为当参与者没有得到物理辅助时,他们的自我效能感较低。本体感觉受损的参与者认为本体感觉训练很有趣,尽管对他们来说更具挑战性,且他们需要更高水平的辅助。
两种训练范式对于慢性中风幸存者来说都是可行的,并且能够实现较高的游戏玩法成功率和训练动机。然而,在提高训练动机方面,物理辅助似乎比虚拟辅助具有优势。本体感觉训练需要高水平的辅助,但即使对于本体感觉较差的人也具有激励作用。
在线版本包含可在10.1186/s12984-025-01667-z获取的补充材料。