• Login
    View Item 
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Dissertations
    • View Item
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA Catalogs

    Statistics

    Display statistics

    A Situational Awareness Enhancing System for Minimally Invasive Surgery Training

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    azu_etd_2435_sip1_m.pdf
    Size:
    2.548Mb
    Format:
    PDF
    Description:
    azu_etd_2435_sip1_m.pdf
    Download
    Author
    Feng, Chuan
    Issue Date
    2007
    Keywords
    MIS
    Simulator
    Surgery Training
    Situational Awareness
    Snesor
    Advisor
    Rozenblit, Jerzy W.
    Committee Chair
    Rozenblit, Jerzy W.
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Minimally Invasive Surgery (MIS) is a surgical technique involving small incisions performed by an endoscope and several long, thin instruments. Because of its minimally invasive nature, MIS minimizes complications and speeds up recovery time compared to the traditional surgery. Unfortunately, from a surgeon's perspective, MIS is much more challenging than conventional surgery. Because the limited vision and sensing feedbacks, MIS a difficult skill for medical students and residents to master.There has been some research on the effectiveness of different kinds of training and guidance. Surgical simulation is increasingly perceived as a valuable addition to traditional medical training methods, although most existing simulators have limitations stemming from either a lack of objective performance assessment or an insufficient relation to the operating room reality.The objective of this research is to design and realize a novel prototype that advances the state of the art in surgical training, assessment, and guidance for MIS. The prototype features micro-sensors embedded into the instruments employed for simulation training. The system provides multiple training scenarios, a high fidelity training environment, repeatable, structured exercises, and objective performance assessment capabilities.The proposed Situational Awareness Enhancing System (SAES) uses a unified framework incorporating perception, comprehension, and projection software modules that provide feedback during the exercises and enable evaluation of the training procedure.A multiple sensor data fusion method was developed to help surgeons efficiently acquire information in real time. The output, "Hybridview", is produced by fusing the information from digital camera and magnetic position sensors, and shows an overlay of the positions of organs and objects with the trajectory of instruments. An intelligent inference engine was designed to formulate an objective standard based on the expertise of senior surgeons and to provide an accurate scoring method. A multi-level fuzzy inference engine and new performance metrics were implemented.To demonstrate the feasibility of the proposed training system, numerous experiments were conducted. The results show that the situational awareness training system for MIS is useful and efficient.
    Type
    text
    Electronic Dissertation
    Degree Name
    PhD
    Degree Level
    doctoral
    Degree Program
    Electrical & Computer Engineering
    Graduate College
    Degree Grantor
    University of Arizona
    Collections
    Dissertations

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.