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Toward Realistic Stitching Modeling and Automation

dc.contributor.advisorPatriciu, Alexandruen_US
dc.contributor.authorHeydari, Khabbaz Faezehen_US
dc.contributor.departmentBiomedical Engineeringen_US
dc.date.accessioned2014-06-18T16:53:55Z
dc.date.available2014-06-18T16:53:55Z
dc.date.created2011-09-16en_US
dc.date.issued2011-10en_US
dc.description.abstract<p>This thesis presents a computational model of the surgical stitching tasks and a path planning algorithm for robotic assisted stitching. The overall goal of the research is to enable surgical robots to perform automatic suturing. Suturing comprises several distinct steps, one of them is the stitching. During stitching, reaching the desired exit point is difficult because it must be accomplished without direct visual feedback. Moreover, the stitching is a time consuming procedure repeated multiple times during suturing. Therefore, it would be desirable to enhance the surgical robots with the ability of performing automatic suturing. The focus of this work is on the automation of the stitching task. The thesis presents a model based path planning algorithm for the autonomous stitching. The method uses a nonlinear model for the curved needle - soft tissue interaction. The tissue is modeled as a deformable object using continuum mechanics tools. This thesis uses a mesh free deformable tissue model namely, Reproducing Kernel Particle Method (RKPM). RKPM was chosen as it has been proven to accurately handle large deformation and requires no re-meshing algorithms. This method has the potential to be more realistic in modeling various material characteristics by using appropriate strain energy functions. The stitching task is simulated using a constrained deformable model; the deformable tissue is constrained by the interaction with the curved needle. The stitching model was used for needle trajectory path planning during stitching. This new path planning algorithm for the robotic stitching was developed, implemented, and evaluated. Several simulations and experiments were conducted. The first group of simulations comprised random insertions from different insertion points without planning to assess the modeling method and the trajectory of the needle inside the tissue. Then the parameters of the simulations were set according to the measured experimental parameters. The proposed path planning method was tested using a surgical ETHICON needle of type SH 1=2 Circle with the radius of 8:88mm attached to a robotic manipulator. The needle was held by a grasper which is attached to the robotic arm. The experimental results illustrate that the path planned curved needle insertions are fifty percent more accurate than the unplanned ones. The results also show that this open loop approach is sensitive to model parameters.</p>en_US
dc.description.degreeMaster of Applied Science (MASc)en_US
dc.identifier.otheropendissertations/6185en_US
dc.identifier.other7191en_US
dc.identifier.other2241826en_US
dc.identifier.urihttp://hdl.handle.net/11375/11198
dc.subjectstitching tasken_US
dc.subjectcomputational modelen_US
dc.subjectpath planning algorithmen_US
dc.subjectrobotic assisted surgeryen_US
dc.subjectdeformable object modelingen_US
dc.subjectReproducing Kernel Particle Methoden_US
dc.subjectBiomechanics and biotransporten_US
dc.subjectBiomedical Engineering and Bioengineeringen_US
dc.subjectEngineeringen_US
dc.subjectBiomechanics and biotransporten_US
dc.titleToward Realistic Stitching Modeling and Automationen_US
dc.typethesisen_US

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