Controller Development to Enable Individualized Assistance in Robotic Ankle Exoskeletons
University of Nebraska
Summary
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.
Description
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.
Eligibility
- Age range
- 19–35 years
- Sex
- All
- Healthy volunteers
- Yes
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 as…
Interventions
- DeviceAdaptive Torque Control System for Ankle Exoskeleton
This intervention uses a robotic ankle exoskeleton equipped with a real-time adaptive controller that adjusts plantarflexion torque based on each participant's walking mechanics. Unlike standard exoskeleton controllers that use fixed or pre-programmed assistance levels, this system employs human-in-the-loop optimization to continuously update torque magnitude and timing during treadmill walking. The controller integrates metabolic estimations, kinematic data, and musculoskeletal modeling to identify individualized assistance patterns that reduce walking effort and improve muscle activation efficiency. Participants complete multiple walking trials while the controller automatically modifies assistance to determine the optimal personalized settings.
Location
- Biomechanics Research Building, University of Nebraska at OmahaOmaha, Nebraska