Feng Guang, Chai Guohong, Zhang Jiaji, Song Tao, Shi Changcheng, Xu Jialin, Zuo Guokun
Laboratory of Advanced Theranostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, China.
Front Hum Neurosci. 2025 Jun 18;19:1571624. doi: 10.3389/fnhum.2025.1571624. eCollection 2025.
The therapeutic effect of robot-assisted training is still indecisive due to the lack of patient-tailored protocols and dose-matched training strategies when compared to traditional treatment. The objective of this study was to investigate the optimal robot-assisted training strategies for the upper limb functional recovery in hemiparetic stroke patients.
A bilateral upper limb rehabilitation robot was employed to execute unilateral and bilateral training. Eighteen able-bodied subjects were recruited to test the effective of robot-assisted training strategies before transferring them to stroke patients. We compared unilateral passive training (UPT), bilateral passive training (BPT), and unilateral active training (UAT) with various feedback types (visual, force, and visual-force, none). These trainings were performed on three kinds of virtually-guided (straight-line, circular, S-shaped) tasks. Tracking error (TE), interactive force (IF) and target muscle activation level were quantified to characterize the motion capability and active participation of subjects.
Results revealed that BPT-visual (0.63 ± 0.26) significantly increased muscle activation level when compared to those of BPT-none (0.45 ± 0.27) and UPT-visual (0.24 ± 0.05) ( < 0.01). UAT with single-modality feedback (visual/force) enabled higher TE (22.5 ± 3.40 mm) and active participation (0.78 ± 0.12) when compared with UAT with multi-modality (visual-force) feedback (TE: 6.6 ± 0.8 mm; activation level: 0.53 ± 0.13) ( < 0.01). The relatively complex circular and S-shaped tasks significantly enhanced the benefits of various training strategies.
The current outcomes provide valuable guidelines for designing individualized robot-assisted training protocols, potentially promoting the clinical rehabilitation effect.
与传统治疗相比,由于缺乏针对患者的方案和剂量匹配的训练策略,机器人辅助训练的治疗效果仍不明确。本研究的目的是探讨偏瘫性卒中患者上肢功能恢复的最佳机器人辅助训练策略。
采用双侧上肢康复机器人进行单侧和双侧训练。招募了18名健康受试者,在将机器人辅助训练策略应用于卒中患者之前,先测试其有效性。我们比较了单侧被动训练(UPT)、双侧被动训练(BPT)和单侧主动训练(UAT),以及不同的反馈类型(视觉、力觉、视觉-力觉、无反馈)。这些训练在三种虚拟引导任务(直线、圆形、S形)上进行。对跟踪误差(TE)、交互力(IF)和目标肌肉激活水平进行量化,以表征受试者的运动能力和主动参与程度。
结果显示,与BPT-无反馈(0.45±0.27)和UPT-视觉反馈(0.24±0.05)相比,BPT-视觉反馈(0.63±0.26)显著提高了肌肉激活水平(P<0.01)。与多模态(视觉-力觉)反馈的UAT(TE:6.6±0.8mm;激活水平:0.53±0.13)相比,单模态反馈(视觉/力觉)的UAT导致更高的TE(22.5±3.40mm)和主动参与度(0.78±0.12)(P<0.01)。相对复杂的圆形和S形任务显著增强了各种训练策略的效果。
目前的结果为设计个性化的机器人辅助训练方案提供了有价值的指导方针,有可能提高临床康复效果。