Chapter

New Frontiers in Artificial Intelligence

Volume 6797 of the series Lecture Notes in Computer Science pp 283-291

Surgical Workflow Monitoring Based on Trajectory Data Mining

  • Atsushi NaraAffiliated withCenter for Spatial Analysis, University of Oklahoma
  • , Kiyoshi IzumiAffiliated withSchool of Engineering, The University of Tokyo & PRESTO, JST.
  • , Hiroshi IsekiAffiliated withInstitute of Advanced Biomedical Engineering and Science, Tokyo Women’s Medical University
  • , Takashi SuzukiAffiliated withInstitute of Advanced Biomedical Engineering and Science, Tokyo Women’s Medical University
  • , Kyojiro NambuAffiliated withResearch and Development Center, Toshiba Medical Systems Corporation
  • , Yasuo SakuraiAffiliated withInstitute of Advanced Biomedical Engineering and Science, Tokyo Women’s Medical University

* Final gross prices may vary according to local VAT.

Get Access

Abstract

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.

Keywords

Surgical Workflow Surgical Management Trajectory Analysis