Short-term Performance-based Error-augmentation versus Error-reduction Robotic Gait Training for Individuals with...

Area of Science:

• Neuroscience
• Robotics
• Rehabilitation Medicine

Background:

• Locomotion training with robotic exoskeletons is crucial for gait retraining in neurologically impaired individuals.
• Identifying effective control algorithms is key to successful rehabilitation following neurological injury, such as stroke.

Purpose of the Study:

• To investigate how two robotic exoskeleton training paradigms, error-augmentation and error-reduction, influence walking patterns in chronic post-stroke individuals.
• To serve as a proof-of-concept for future robotic-assisted locomotion training strategies after stroke.

Main Methods:

• Four chronic post-stroke individuals were trained to match a prescribed walking pattern template using robotic forces.
• Robotic forces were applied to either decrease (error-reduction) or increase (error-augmentation) deviations in ankle malleolus paths.
• Subject performance was quantified by measuring the deviation between actual and target malleolus paths.

Main Results:

• Error-reduction training resulted in minimal modification of gait patterns, with one subject showing a 16% reduction in deviation and another a 12% increase.
• Error-augmentation training led to more significant changes, with one subject achieving 58% reduced deviation and another a 37% increase in deviation.
• Findings indicate error-augmentation may be more effective in promoting gait pattern modification compared to error-reduction.

Conclusions:

• Error-reduction force fields appear to have limited impact on modifying post-stroke gait patterns.
• Error-augmentation force fields show potential in guiding gait towards or even beyond a target walking template.
• Further research is needed to assess the long-term effects of these training paradigms on over-ground walking and functional recovery.