Reducing robotic guidance during robot-assisted gait training improves gait function: a case report on a stroke survivor

Abstract

Objective: To test the feasibility of patient-cooperative robotic gait training for improving locomotor function of a chronic stroke survivor with severe lower-extremity motor impairments.

Design: Single-subject crossover design.

Setting: Performed in a controlled laboratory setting.

Participant: A 62-year-old man with right temporal lobe ischemic stroke was recruited for this study. The baseline lower-extremity Fugl-Meyer score of the subject was 10 on a scale of 34, which represented severe impairment in the paretic leg. However, the subject had a good ambulation level (community walker with the aid of a stick cane and ankle-foot orthosis) and showed no signs of sensory or cognitive impairments.

Interventions: The subject underwent 12 sessions (3 times per week for 4wk) of conventional robotic training with the Lokomat, where the robot provided full assistance to leg movements while walking, followed by 12 sessions (3 times per week for 4wk) of patient-cooperative robotic control training, where the robot provided minimal guidance to leg movements during walking.

Main outcome measures: Clinical outcomes were evaluated before the start of the intervention, immediately after 4 weeks of conventional robotic training, and immediately after 4 weeks of cooperative control robotic training. These included: (1) self-selected and fast walking speed, (2) 6-minute walk test, (3) Timed Up & Go test, and (4) lower-extremity Fugl-Meyer score.

Results: Results showed that clinical outcomes changed minimally after full guidance robotic training, but improved considerably after 4 weeks of reduced guidance robotic training.

Conclusions: The findings from this case study suggest that cooperative control robotic training is superior to conventional robotic training and is a feasible option to restoring locomotor function in ambulatory stroke survivors with severe motor impairments. A larger trial is needed to verify the efficacy of this advanced robotic control strategy in facilitating gait recovery after stroke.