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Design of EMG-driven Musculoskeletal Model for Volitional Control of a Robotic Ankle Prosthesis

Chinmay Shah, Aaron Fleming, Varun Nalam, Ming Liu, He Huang

Year
2022
Citations
14

Abstract

Existing robotic lower-limb prostheses use autonomous control to address cyclic, locomotive tasks, but are inadequate in adapting to variations in non-cyclic and unpredictable tasks. This study aims to address this challenge by designing a novel electromyography (EMG)-driven musculoskeletal model for volitional control of a robotic ankle-foot prosthesis. The proposed controller ensures continuous control of the device, allowing users to freely manipulate the prosthesis behavior. A Hill-type muscle model was implemented to model a dorsiflexor and a plantarflexor to function around a virtual ankle joint. The model parameters for a subject specific model was determined by fitting the model to the experimental data collected from an able-bodied subject. EMG signals recorded from antagonist muscle pairs were used to activate the virtual muscle models. This model-based approach was then validated via offline simulations and real-time prosthesis control. Additionally, the feasibility of the proposed prosthesis control on assisting the user's functional tasks was demonstrated. The present control may further improve the function of robotic prosthesis for supporting versatile activities in individuals with lower-limb amputations.

Keywords

AnkleElectromyographyProsthesisController (irrigation)Computer scienceSimulationPhysical medicine and rehabilitationArtificial intelligenceMedicine

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