Effective unilateral/bilateral robot-assisted training for upper limb motor function rehabilitation: a cross-sectional study

TL;DR

This study compares different robot-assisted training methods for upper limb rehabilitation in stroke patients, finding that specific training strategies and feedback types improve muscle activation and performance.

Contribution

The study identifies optimal robot-assisted training strategies and feedback types for enhancing upper limb rehabilitation in stroke patients.

Findings

Bilateral passive training with visual feedback significantly increased muscle activation compared to other passive training methods.

Unilateral active training with single-modality feedback improved task performance and active participation more than multi-modality feedback.

Complex tasks like circular and S-shaped paths enhanced the effectiveness of various training strategies.

Abstract

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) (p < 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) (p < 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.

Figures