Patients with stroke can experience a drastic change in their body representation (BR), beyond the physical and psychological consequences of stroke itself. Noteworthy, the misperception of BR could affect patients' motor performance even more. Our study aimed at evaluating the usefulness of a robot-aided gait training (RAGT) equipped with augmented visuomotor feedback, expected to target BR (RAGT + VR) in improving lower limb sensorimotor function, gait performance (using Fugl-Meyer Assessment scale for lower extremities, FMA-LE), and BR (using the Body Esteem Scale—BES- and the Body Uneasiness Test—BUT), as compared to RAGT − VR. We also assessed the neurophysiologic basis putatively subtending the BR-based motor function recovery, using EEG recording during RAGT. Forty-five patients with stroke were enrolled in this study and randomized with a 1:2 ratio into either the RAGT + VR (n = 30) or the RAGT − VR (n = 15) group. The former group carried out rehabilitation training with the Lokomat©Pro; whereas, the latter used the Lokomat©Nanos. The rehabilitation protocol consisted of 40 one-hour training sessions. At the end of the training, the RAGT + VR improved in FMA-LE (p < 0.001) and BR (as per BES, (p < 0.001), and BUT, (p < 0.001)) more than the RAGT- did (p < 0.001). These differences in clinical outcomes were paralleled by a greater strengthening of visuomotor connectivity and corticomotor excitability (as detected at the EEG analyses) in the RAGT + VR than in the RAGT − VR (all comparisons p < 0.001), corresponding to an improved motor programming and execution in the former group.

We may argue that BR recovery was important concerning functional motor improvement by its integration with the motor control system. This likely occurred through the activation of the Mirror Neuron System secondary to the visuomotor feedback provision, resembling virtual reality. Last, our data further confirm the important role of visuomotor feedback in post-stroke rehabilitation, which can achieve better patient-tailored improvement in functional gait by means of RAGT + VR targeting BR.

中风患者的身体表征 (BR) 可能会发生巨大变化，这超出了中风本身的生理和心理后果。值得注意的是，对 BR 的误解可能会更大程度地影响患者的运动表现。我们的研究旨在评估配备增强视觉运动反馈的机器人辅助步态训练 (RAGT) 的有用性，该训练有望针对 BR (RAGT + VR) 改善下肢感觉运动功能、步态表现（使用 Fugl-Meyer 评估量表来降低四肢，FMA-LE）和 BR（使用身体自尊量表-BES-和身体不适测试-BUT），与 RAGT-VR 相比。我们还评估了假定对基于 BR 的运动功能恢复的神经生理学基础，在 RAGT 期间使用脑电图记录。45 名卒中患者参加了这项研究，并以 1:2 的比例随机分为 RAGT + VR (n = 30) 或 RAGT - VR (n = 15) 组。前一组使用 Lokomat©Pro 进行康复训练；而后者则使用 Lokomat©Nanos。康复方案包括 40 个一小时的训练课程。训练结束时，RAGT + VR 在 FMA-LE 中得到提升( p < 0.001) 和 BR (根据 BES，(p < 0.001) 和 BUT，(p < 0.001)) 比 RAGT-做的 (p < 0.001) 更多。与 RAGT - VR 相比，RAGT + VR 中的视觉运动连接性和皮质运动兴奋性（如在 EEG 分析中检测到的）的这些临床结果差异更大（所有比较 p < 0.001），对应于改进的运动编程并在前一组执​​行。

我们可能会争辩说，BR 恢复对于通过与电机控制系统集成来改善功能性电机非常重要。这很可能是通过激活继视觉运动反馈提供的镜像神经元系统而发生的，类似于虚拟现实。最后，我们的数据进一步证实了视觉运动反馈在中风后康复中的重要作用，通过 RAGT + VR 靶向 BR，可以更好地改善患者的功能步态。