An optimal motion planning method for computer-assisted surgical training

Liana Napalkova, Jerzy W. Rozenblit, George Hwang, Allan J. Hamilton, Liana Suantak

    Research output: Contribution to journalArticleResearchpeer-review

    15 Citations (Scopus)

    Abstract

    © 2014 Elsevier B.V. All rights reserved. This paper focuses on the development and validation of an optimal motion planning method for computer-assisted surgical training. The context of this work is the development of new-generation systems that combine artificial intelligence and computer vision techniques in order to adjust the learning process to specific needs of a trainee, while preventing a trainee from the memorization of particular task settings. The problem described in the paper is the generation of shortest, collision-free trajectories for laparoscopic instrument movements in the rigid block world used for hand-eye coordination tasks. Optimal trajectories are displayed on a monitor to provide continuous visual guidance for optimal navigation of instruments. The key result of the work is a framework for the transition from surgical training systems in which users are dependent on predefined task settings and lack guidance for optimal navigation of laparoscopic instruments, to the so called intelligent systems that can potentially deliver the utmost flexibility to the learning process. A preliminary empirical evaluation of the developed optimal motion planning method has demonstrated the increase of total scores measured by total time taken to complete the task, and the instrument movement economy ratio. Experimentation with different task settings and the technical enhancement of the visual guidance are subjects of future research.
    Original languageEnglish
    Pages (from-to)889-899
    JournalApplied Soft Computing Journal
    Volume24
    DOIs
    Publication statusPublished - 1 Jan 2014

    Keywords

    • Computer-assisted surgical training
    • Laparoscopic surgery
    • Optimal motion planning
    • Performance assessment

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