Methodology of Robot-Assisted Tool Manipulation for Virtual Reality Based Dissection

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dc.contributor.advisorHu, Yaoping
dc.contributor.authorTrejo Torres, Fernando Javier
dc.contributor.committeememberSesay, Abu B.
dc.contributor.committeememberWestwick, David T.
dc.contributor.committeememberChan, Sonny
dc.contributor.committeememberLiu, Peter J.
dc.date2019-06
dc.date.accessioned2019-04-01T18:36:36Z
dc.date.available2019-04-01T18:36:36Z
dc.date.issued2019-03-29
dc.description.abstractRobot-assisted (RA) surgery employs a master-slave system, in which a surgeon's hand manoeuvres the stylus of a hand controller (master) mapped at the operation site to indirectly manipulate a surgical tool attached to the end-effector of a robot (slave). Hence, RA surgery has two drawbacks. Firstly, the transfer of tool-tissue interaction forces to a surgeon is either absent or inaccurate. Secondly, RA surgery incorporates motion coupling (MC) and motion coupling plus orientation match (MC+OM) as indirect modes of tool manipulation, which disregard a pose (position and orientation) match (PM) between the mapped stylus and the tool. This may cause inadvertent tissue trauma during tasks like dissection, which spends ~35.0% of surgery time. Due to the potential of virtual reality (VR) based surgical training, this thesis presents a methodology to address the drawbacks on a VR simulator of soft-tissue dissection. The methodology comprises the formulations and evaluations of an analytic model that estimates dissection forces; and a PM algorithm. The simulator interfaced with the haptic device PHANToM Premium 1.5/6DOF (as a hand controller) to deliver the model forces, and incorporated the kinematics of the device and neuroArm (a neurosurgery robot) for the PM algorithm. The evaluation of the model for estimating dissection forces collected at the tool speeds of 0.10, 1.27, and 2.54 cm/s indicated a force estimation > 80.0%, a computation time < 1.0 ms (the device's update period), and a bandwidth < 30.0 Hz (the device's bandwidth). Moreover, the model lessened cognitive workload for dissections executed at 0.10 cm/s. The evaluation of the PM algorithm revealed a position match < 30.0 µm (the position resolution of the device and neuroArm), an orientation match < 10.0° (to minimize the surgeon's disorientation), and a computation time < 500.0 µs (a half of the device's update period). Additionally, the algorithm became useful to maintain an accurate tool speed and reduce tissue trauma for dissections performed at 0.10 cm/s. The outcomes imply the suitability of the methodology for VR-based RA dissection and their potential to suggest guidelines for VR-based RA dissection training.en_US
dc.identifier.citationTrejo Torres, F. J. (2019). Methodology of robot-assisted tool manipulation for virtual reality based dissection (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/36336
dc.identifier.urihttp://hdl.handle.net/1880/110132
dc.language.isoenen_US
dc.publisher.facultySchulich School of Engineeringen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectvirtual realityen_US
dc.subjecthapticsen_US
dc.subjectrobot-assisted surgeryen_US
dc.subjectmaster-slave systemen_US
dc.subjectsoft-tissue dissectionen_US
dc.subjecttool-tissue interaction forcesen_US
dc.subjectanalytic modelen_US
dc.subjectsurgical tool manipulationen_US
dc.subjectpose matchen_US
dc.subject.classificationEngineering--Biomedicalen_US
dc.subject.classificationEngineering--Electronics and Electricalen_US
dc.subject.classificationRoboticsen_US
dc.titleMethodology of Robot-Assisted Tool Manipulation for Virtual Reality Based Dissectionen_US
dc.typedoctoral thesisen_US
thesis.degree.disciplineEngineering – Electrical & Computeren_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
ucalgary.item.requestcopytrue
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