Modelling a biomechanical system and an afferent nervous system in order to simulate real response in stroke patients
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Inclou dades d'ús des de 2022
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hdl:2117/368290
Tipus de documentProjecte Final de Màster Oficial
Data2022-04-29
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Abstract
This main goal of this project is to model a digital twin of a stroke patient in order to see a virtual response of the muscle and brain activity when performing exercises with a rehabilitation exoskeleton. In order to do that, a musculoskeletal system, an exoskeleton and an afferent system were modelled. Additionally, these have to be connected in a closed loop with a virtual brain. For the musculoskeletal system, an open-source software, OpenSim, has been used to create a model of the upper limb, wrist and fingers with an exoskeleton. The model has the ability to simulate the muscle activation, length and force of each muscle and the actuator when performing an exercise. On the other hand, the interconnection with the musculoskeletal model and the CNS will be done with an adapted platform, the NeuroRobotics Platform, a project from the Human Brain Project. This platform enables to control a robot, for example the model from OpenSim, through a virtual brain, a module that simulates the brain. Additionally, in order to provide feedback to the virtual brain a sensorial system has been created following the same methodology of a real biological system. The sensorial organs of the muscles that provide information about length, velocity or tension have been modelled in Simulink, an extension of Matlab, which provides tools to model signals with block diagrams. The results of the behaviour of the model and the modelling of signals were similar as a real subject. This project is very extensive and horizontal and it was not possible to deepen in the different blocks worked. However, the main objectives of the project have been achieved that were the creation of the different models in order to import then to the platform.
TitulacióMÀSTER UNIVERSITARI EN NEUROENGINYERIA I REHABILITACIÓ (Pla 2020)
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