Development of a Real-time Controller to Estimate Walking Performance Using a Bilateral Ankle Exoskeleton

Controller Development to Enable Individualized Assistance in Robotic Ankle Exoskeletons

This study is developing and testing a new controller for a robotic ankle exoskeleton (Biomotum) that can adjust itself in real time to better support people while they walk. The system learns how each person moves and automatically changes the amount and timing of assistance to make walking feel easier and more efficient. By using information from the person wearing the device, the exoskeleton can quickly find the level of support that works best for them. The long-term goal is to create personalized walking assistance that can help people with mobility limitations move more comfortably and with less effort.

This project aims to develop and test a real-time adaptive controller for a robotic ankle exoskeleton (Biomotum) that personalizes assistance to each user by minimizing metabolic cost and optimizing muscle activation patterns during walking. Using human-in-the-loop optimization and advanced musculoskeletal modeling, the controller will dynamically adjust torque magnitude and timing to achieve optimal performance more quickly than current methods.

Inclusion Criteria:

• able to walk independently on a treadmill for 10 minutes,
• free of neurological, cardiovascular, pulmonary, or musculoskeletal conditions that limit walking and exercising,
• no current lower extremity pain or injury,
• able to wear an exoskeleton and safety harness, can provide informed consent

Exclusion Criteria:

• history of neurological disease that affected gait or balance,
• current or recent lower extremity musculoskeletal injury or surgery,
• chronic lower extremity pain during walking,
• inability to participate in moderate-intensity exercise,
• require an assistive device for walking,
• any metabolic or systemic diseases that may be exacerbated by exercise