Surgical workflow monitoring based on trajectory data mining

Atsushi Nara, Kiyoshi Izumi, Hiroshi Iseki, Takashi Suzuki, Kyojiro Nambu, Yasuo Sakurai

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    15 Citations (Scopus)


    This research aims at investigating intermediate-scale workflows using the surgical staff's movement pattern. In this study, we have introduced an ultrasonic location aware system to monitor intraoperative movement trajectories on surgical staffs for the workflow analysis. And we developed trajectory data mining for surgical workflow segmentation, and analyzed trajectory data with multiple cases. As a result, in 77.18% of total time, a kind of current operation stage could be correctly estimated. With high accuracy 85.96%, the estimation using trajectory data was able to distinguish whether a current 5 minutes was transition time from one stage to another stage or not.. Based on these results, we are implementing the surgery safe support system that promotes safe & efficient surgical operations.

    Original languageEnglish
    Title of host publicationNew Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers
    Number of pages9
    Publication statusPublished - 2011 Nov 29
    Event2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010 - Tokyo, Japan
    Duration: 2010 Nov 182010 Nov 19

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume6797 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010


    • Surgical Management
    • Surgical Workflow
    • Trajectory Analysis

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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