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Development of an upper limb exoskeleton digital twin in immersive virtual reality
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Resumo(s)
Research suggests that for stroke patients, high-intensity training is critical for patient recovery. This can
be provided by robotic rehabilitation in combination with virtual reality (VR), enabling highly intensive and
motivating exercises.
The more motivated the patients are, the more engaged they will be in performing the exercises, ultimately
leading to better motor function improvement. However, in conventional therapy and most research, the robot is
usually not visualized, which can lead to a discrepancy between what the user sees and feels.
In this work, we present the development of a digital twin of an upper limb rehabilitation exoskeleton in
VR. The user interacted with the virtual environment (VE) through a head-mounted display and manipulation of
the real robot. To create a more functional and realistic interaction with the VE, the exoskeleton was previously
upgraded with one more degree of freedom, by integrating a novel hand module, allowing the user to perform
grasping movements. In addition, a prototype of a VR game aimed at the interaction between the digital twin and
the VE was developed, as well as preliminary measurements of the kinematic accuracy of the digital twin and its
kinematic model.
When the user moved the rehabilitation robot, the digital twin was found to move accordingly, mimicking
the movements of all joints. With only a small position offset, it can be concluded that despite the exoskeleton’s
complexity, the implementation was successful, and this offset will probably not reduce the immersion or
embodiment of the user.
The developed visualization enables the possibility of studying the influence of digital twins on motor
learning. Although future work is needed, namely adjusting the joints of the digital twin, and testing the
visualization model on real patients, this study should be considered as a starting point to allow the development
of more effective rehabilitation exercises.
Descrição
Tese de mestrado, Engenharia Biomédica e Biofísica, 2023, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
AVC membro superior reabilitação robótica realidade virtual gémeo digital Teses de mestrado - 2023