Tuning of robotic therapy controllers for stroke gait: Using isometrically constrained EMG modular structures

Area of Science:

• Biomedical Engineering
• Rehabilitation Science
• Neuroscience

Background:

• Electromyography (EMG) based controllers offer promise for post-stroke gait rehabilitation and assistive devices.
• Integrating stroke-specific neuromuscular patterns into active gait assistance controllers remains an underexplored area.
• Understanding muscle activation variability is crucial for developing effective gait rehabilitation strategies.

Purpose of the Study:

• To investigate the variability between lower limb muscle activation patterns during isometric tasks and dynamic gait subtasks.
• To explore the potential of using isometric muscle synergies for designing active gait assistance controllers.
• To provide preliminary evidence for reconstructing spatio-temporal patterns of healthy locomotion.

Main Methods:

• Utilized matrix factorization algorithms to analyze lower limb muscle activation patterns.
• Compared muscle coordination patterns during discrete isometric control objectives with dynamic subtasks during treadmill gait.
• Focused on identifying common muscle synergies underlying both types of tasks.

Main Results:

• Identified common muscle coordination patterns present in both isometric and dynamic gait submovements.
• Demonstrated that these common patterns can be used to reconstruct spatio-temporal patterns relevant to healthy locomotion.
• Provided preliminary evidence of variability between isometric and dynamic muscle activation patterns.

Conclusions:

• Isometric muscle synergies may be sufficient for tuning adaptive controllers in gait orthosis.
• This approach could help address disruptive linkages in EMG control signals impacting gait dysfunction.
• The findings support the potential of using isometric contractions to inform the design of advanced gait rehabilitation technologies.