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Neuro-Robotics System for Intelligent Positioning of Deep Brain Stimulation Electrodes

datacite.subject.fosDepartamento de Físicapt_PT
dc.contributor.advisorCunha, João Paulo Trigueiros da Silva
dc.contributor.advisorEvans, Guiomar Gaspar de Andrade, 1966-
dc.contributor.authorBaptista, Tânia Sousa
dc.date.accessioned2022-07-22T09:30:14Z
dc.date.available2022-07-22T09:30:14Z
dc.date.issued2022
dc.date.submitted2022
dc.descriptionTese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica) Universidade de Lisboa, Faculdade de Ciências, 2022pt_PT
dc.description.abstractThe 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.pt_PT
dc.identifier.tid203218248pt_PT
dc.identifier.urihttp://hdl.handle.net/10451/53908
dc.language.isoengpt_PT
dc.subjectNeurocirurgia robóticapt_PT
dc.subjectestimulação cerebral profundapt_PT
dc.subjectrigidez do punhopt_PT
dc.subjectfantoma antropomórfico do crâniopt_PT
dc.subjectsimulador de robóticapt_PT
dc.subjectTeses de mestrado - 2022pt_PT
dc.titleNeuro-Robotics System for Intelligent Positioning of Deep Brain Stimulation Electrodespt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameTese de mestrado integrado em Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica)pt_PT

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