ArticleFrontiers in neurorobotics2023
Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements.
Article in Frontiers in neurorobotics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- An EEG-EMG-kinematics dataset from wrist pointing tasks for biomarker research in neurorehabilitation.Scientific data · 2026Article
- Hybrid 12-Month Exoskeleton Training with Percutaneous Epidural Stimulation After Spinal Cord Injury.Life (Basel, Switzerland) · 2026Article
- A multifaceted hybrid ES-robotic device for gait training in individuals with neurological disorders.Nature communications · 2025Article
- Simplified control of neuromuscular stimulation systems for restoration of reach with limb stiffness as a modifiable degree of freedom.Journal of neural engineering · 2025Article
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Authors and funding
4 authors.
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Abstract
Introduction: Individuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system. Methods: In this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories. Results: The MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone. Discussion: To realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities.
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