Robotic systems and Functional Electrical Stimulation (FES) are common technologies exploited in motor rehabilitation. However, they present some limits. To overcome the weaknesses of both approaches, hybrid cooperative devices have been developed, which combine the action of the robot and that of the electrically stimulated muscles on the same joint. In this work, we present a novel adaptive cooperative controller for the rehabilitation of the upper limb. The controller comprises an allocator - which breaks down the reference torque between the motor and the FES a-priori contributions based on muscle fatigue estimation - an FES closed-loop controller, and an impedance control loop on the motor to correct trajectory tracking errors. The controller was tested in simulation environment reproducing elbow flexion/extension movements. Results showed that the controller could reduce motor torque requirements with respect to the motor-only case, at the expense of trajectory tracking performance. Moreover, it could improve fatigue management with respect to the FES-only case. In conclusion, the proposed control strategy provides a good trade-off between motor torque consumption and trajectory tracking performance, while the allocator manages fatigue-related phenomena.Clinical relevance - The use of allocation proves to be effective in both reducing motor torque and FES-induced muscle fatigue and might be an effective solution for hybrid FES-robotic systems.

Adaptive Cooperative Control for Hybrid FES-Robotic Upper Limb Devices: A Simulation Study

Bardi E.;Dalla Gasperina S.;Pedrocchi A.;Ambrosini E.
2021

Abstract

Robotic systems and Functional Electrical Stimulation (FES) are common technologies exploited in motor rehabilitation. However, they present some limits. To overcome the weaknesses of both approaches, hybrid cooperative devices have been developed, which combine the action of the robot and that of the electrically stimulated muscles on the same joint. In this work, we present a novel adaptive cooperative controller for the rehabilitation of the upper limb. The controller comprises an allocator - which breaks down the reference torque between the motor and the FES a-priori contributions based on muscle fatigue estimation - an FES closed-loop controller, and an impedance control loop on the motor to correct trajectory tracking errors. The controller was tested in simulation environment reproducing elbow flexion/extension movements. Results showed that the controller could reduce motor torque requirements with respect to the motor-only case, at the expense of trajectory tracking performance. Moreover, it could improve fatigue management with respect to the FES-only case. In conclusion, the proposed control strategy provides a good trade-off between motor torque consumption and trajectory tracking performance, while the allocator manages fatigue-related phenomena.Clinical relevance - The use of allocation proves to be effective in both reducing motor torque and FES-induced muscle fatigue and might be an effective solution for hybrid FES-robotic systems.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
978-1-7281-1179-7
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1203103
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