American journal of translational research · 2026
Long-term impact of robot-assisted training on walking pattern reconstruction in chronic stroke survivors: insights from multiparametric gait analysis.
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Qin Zujie, Cao Qinhua, Wang Jie, Jiang Peiyu, Sha Xueping
Аннотация
AIMS: To determine whether robot-assisted lower-limb training promotes superior walking pattern reconstruction in chronic stroke survivors, as quantified by multiparametric gait analysis and supported by concurrent improvements in motor, balance, and functional outcomes.
METHODS: In this retrospective observational study, 80 patients with chronic stroke sequelae treated between January 2024 and January 2026 were allocated according to routine rehabilitation exposure to a control group (n = 45) or an observation group (n = 35); the primary endpoint was post-intervention gait remodeling, defined by change in gait speed and multiparametric spatiotemporal gait indices, while secondary endpoints included lower-limb motor recovery, spasticity, balance, functional independence, clinically meaningful responder status, and multivariable analysis of determinants of gait-speed change as the principal marker of walking pattern reconstruction.
RESULTS: After 10 weeks, the observation group showed significantly greater improvement than the control group in lower-limb motor function, including Fugl Meyer Assessment of the Lower Extremity total, proximal, and distal subscores, Timed Up and Go performance, and 10-m walking speed (all P < 0.001). Spasticity was also more effectively reduced, with lower Modified Ashworth Scale composite and segment-specific scores (P = 0.002 to < 0.001). In addition, balance, spatiotemporal gait parameters, and motor-related functional independence improved more markedly in the observation group (all P < 0.001 for key outcomes).
CONCLUSION: Robot-assisted lower-limb rehabilitation, when added to conventional therapy, significantly enhanced gait remodeling, motor recovery, spasticity reduction, balance performance, and locomotion-related independence in chronic stroke survivors, supporting its value as an effective strategy for promoting more physiological and clinically meaningful walking restoration after stroke.
METHODS: In this retrospective observational study, 80 patients with chronic stroke sequelae treated between January 2024 and January 2026 were allocated according to routine rehabilitation exposure to a control group (n = 45) or an observation group (n = 35); the primary endpoint was post-intervention gait remodeling, defined by change in gait speed and multiparametric spatiotemporal gait indices, while secondary endpoints included lower-limb motor recovery, spasticity, balance, functional independence, clinically meaningful responder status, and multivariable analysis of determinants of gait-speed change as the principal marker of walking pattern reconstruction.
RESULTS: After 10 weeks, the observation group showed significantly greater improvement than the control group in lower-limb motor function, including Fugl Meyer Assessment of the Lower Extremity total, proximal, and distal subscores, Timed Up and Go performance, and 10-m walking speed (all P < 0.001). Spasticity was also more effectively reduced, with lower Modified Ashworth Scale composite and segment-specific scores (P = 0.002 to < 0.001). In addition, balance, spatiotemporal gait parameters, and motor-related functional independence improved more markedly in the observation group (all P < 0.001 for key outcomes).
CONCLUSION: Robot-assisted lower-limb rehabilitation, when added to conventional therapy, significantly enhanced gait remodeling, motor recovery, spasticity reduction, balance performance, and locomotion-related independence in chronic stroke survivors, supporting its value as an effective strategy for promoting more physiological and clinically meaningful walking restoration after stroke.