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Neuro-Robotics System for Intelligent Positioning of Deep Brain Stimulation Electrodes
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Autores
Resumo(s)
The iHandU system is a wearable device that quantitatively evaluates changes in wrist rigidity during
Deep Brain Stimulation (DBS) surgery, allowing clinicians to find optimal stimulation settings that reduce
patient symptoms. Robotic accuracy is also especially relevant in DBS surgery, as accurate electrode
placement is required to increase effectiveness and reduce side effects.
The main objective of this work is to integrate the advantages of each system in a closed-loop system,
where a robotic arm positions the tools along the planned trajectory and seeks the best stimulation site
according to wrist rigidity improvement given by the iHandU system. For this purpose, we developed
and implemented a contact-based registration approach and a robot trajectory control application.
As an initial experimental approach, a robotic simulator to analyze the solution’s reliability and
reachability was used. Then, a comparative analysis of a Leksell stereotactic frame and neuro-robotic
system accuracies was performed using a lab-made phantom.
Simulation experiments show that the neuro-robotic system positions the robot tool as expected. The
in vitro experimental validation shows that the neuro-robotic system reached 9 out of 10 trajectories, while
the stereotactic frame reached all trajectories. There are significant differences in accuracy errors between
these trajectories, which can be explained by the high correlation of the neuro-robotic system errors and
the distance from the trajectory to the origin of the Leksell coordinate system (ρ = 0.72). The trajectory
angulation may also have influenced the accuracy errors. The registration process quality, calibration
of the robot’s tools, and the robot’s volumetric accuracy may have been factors that interfered with the
application accuracy. Overall accuracy is comparable to existing neuro-robotic systems, achieving a
deviation of (1.0±0.5) mm at the target point, which compares favorably to other works.
Descrição
Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica) Universidade de Lisboa, Faculdade de Ciências, 2022
Palavras-chave
Neurocirurgia robótica estimulação cerebral profunda rigidez do punho fantoma antropomórfico do crânio simulador de robótica Teses de mestrado - 2022