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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-03262025-144428


Thesis type
Tesi di laurea magistrale
Author
BALESTRI, MARCO
URN
etd-03262025-144428
Thesis title
A Magnetically Guided Robotic System for Electrode Implantation in Deep Brain Stimulation
Department
INGEGNERIA CIVILE E INDUSTRIALE
Course of study
INGEGNERIA MECCANICA
Supervisors
relatore Prof. Artoni, Alessio
supervisore Prof. Nelson, Bradley
Keywords
  • deep brain stimulation
  • ex-vivo experiments
  • magnetic actuation
  • medical robotics
  • soft robotics
Graduation session start date
16/04/2025
Availability
Withheld
Release date
16/04/2065
Summary
Soft magnetically actuated robots represent an excellent solution for minimally invasive surgery due to the reduced tissue stress, inherent capability of miniaturiaztion and ability to be controlled by magnetic fields. A treatment that would benefit from these characteristics is Deep Brain Stimulation, an advanced neurosurgical technique based on the implantation of an electrode in specific brain regions to modulate neural activity, e.g. to treat Parkinson’s Disease. However, current DBS procedure relies on rigid, straight needles, limiting insertion trajectories and increasing risks of damaging critical brain structures.
This thesis introduces a magnetically guided robotic system able to implant DBS electrodes following curved trajectories, avoiding critical anatomical obstacles. The novel robotic implantation concept is first presented, followed by details on the design and prototyping.
The electrode is implanted using a soft needle with an articulated magnetic tip, guided by magnetic fields and advanced while maintaining electrode connection to an electrophysiology system for real-time neurological assessment. Then, the electrode is delivered and the magnetic needle is helically retracted to minimize friction. The entire procedure is remotely controlled by the surgeon, enabling precise steering in the space. Finally, ex-vivo experiments on pig brains are presented to validate the system’s accuracy and improved steerability compared to current DBS methods.
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