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  4. Mechanical and Computational Design of Continuum Robots for Minimally Invasive Lung Interventions

Mechanical and Computational Design of Continuum Robots for Minimally Invasive Lung Interventions

AUTHORS

Rox Margaret F .

ABSTRACT

The central motivation for this dissertation is to provide improved tools for the diagnosis and treatment of lung disease. Lung cancer, in particular, has the highest death rate of any type of cancer, and early intervention is critical for positive outcomes. Proximity to the heart makes the lungs especially difficult to access, as the ribs, sternum, and chest wall must either be passed through or circumvented, and blood vessels and airways present an additional challenge of navigation. This work examines new mechanical and computational designs of continuum robots that will increase safe, minimally invasive access to the lungs for both diagnosis and treatment. Continuum robots are continuous backbone structures that are highly dexterous, miniaturizable, and compliant, making them well-suited to medical applications where delicate structures in the body require complex procedures. This dissertation focuses on two particular lung applications and two different types of continuum robots: steerable needles for peripheral lung lesion targeting and tendon-driven robots for lung tissue resection. First, this work examines a new steerable needle design that enables enhanced bronchoscopic targeting of lung nodules for taking a biopsy or delivering treatment. As bronchoscopic interventions are not always possible, this dissertation also presents a new tendon-driven robot design intended to reduce incision size for lung access through the ribs. Extending further into this application, the final chapter examines a new parameterization of tendon routing for tendon-driven robots that enables the use of computational design techniques to replicate the actions of a da Vinci robot during surgical lung procedures. Overall, the work in this document demonstrates methods for designing continuum robots that are capable of improving the current state-of-the-art in diagnosis and treatment for lung interventions.

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