This study systematically compares the efficacy of robotic-assisted gait training (RAGT) with exoskeletons to traditional gait training (TGT) for lower limb rehabilitation after stroke, focusing on motor recovery, neuroplasticity, and muscle function. A comprehensive systematic review was conducted across PubMed, Scopus, Web of Science, IEEE Xplore and Google Scholar for studies published between 2004 and 2024 following the PRISMA guidelines. A total of 86 studies were selected based on strict inclusion criteria, covering moderate to severe stroke patients undergoing RAGT, TGT, or combined interventions. Outcome metrics included gait symmetry, walking speed, neuroplasticity biomarkers (e.g., BDNF, fMRI), and muscle strength indicators. This systematic review was pre-registered with PROSPERO (ID: CRD420261333541). RAGT demonstrated superior improvements in gait symmetry index (+ 99.8% trajectory accuracy), walking speed (+ 20%), and muscle strength via high-intensity, repeatable training. TGT excelled in promoting active participation, cortical engagement, and functional independence, particularly in activities of daily living. Neuroplasticity analysis revealed RAGT enhanced spinal-brainstem rhythmic-ity, while TGT reinforced cortical-cerebellar motor planning. Muscle recovery was accelerated by RAGT through anti-gravitational support, though TGT better preserved natural movement patterns and coordination. RAGT and TGT exhibit complementary strengths in stroke rehabilitation. Integrating RAGT’s high-intensity, objective training with TGT’s adaptive, patient-centered approach represents a promising direction for personalized, AI-enhanced neurorehabilitation strategies.
Xu et al. (Fri,) studied this question.