This paper presents a myoelectric control of an arm exoskeleton designed for rehabilitation. A four-muscles-based NeuroMusculoSkeletal (NMS) model was implemented and optimized using genetic algorithms to adapt the model to different subjects. The NMS model is able to predict the shoulder and elbow torques which are used by the control algorithm to ensure a minimal force of interaction. The accuracy of the method is assessed through validation experiments conducted with two healthy subjects performing free movements along the pseudo-sagittal plane. The experiments show promising results for our approach showing its potential for being introduced in a rehabilitation protocol.

A neuromusculoskeletal model of the human upper limb for a myoelectric exoskeleton control using a reduced number of muscles

LOCONSOLE, CLAUDIO;
2015-01-01

Abstract

This paper presents a myoelectric control of an arm exoskeleton designed for rehabilitation. A four-muscles-based NeuroMusculoSkeletal (NMS) model was implemented and optimized using genetic algorithms to adapt the model to different subjects. The NMS model is able to predict the shoulder and elbow torques which are used by the control algorithm to ensure a minimal force of interaction. The accuracy of the method is assessed through validation experiments conducted with two healthy subjects performing free movements along the pseudo-sagittal plane. The experiments show promising results for our approach showing its potential for being introduced in a rehabilitation protocol.
2015
9781479966240
Exoskeleton
Genetic Algorithm
Myoelectric Control
NeuroMusculoSkeletal Model
sEMG signals
Upper Limb
Artificial Intelligence
Human-Computer Interaction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/1913
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