Surgical workflow monitoring based on trajectory data mining

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

*この研究の対応する著者

研究成果: Conference contribution

17 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルNew Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers
ページ283-291
ページ数9
DOI
出版ステータスPublished - 2011
外部発表はい
イベント2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010 - Tokyo, Japan
継続期間: 2010 11月 182010 11月 19

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6797 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010
国/地域Japan
CityTokyo
Period10/11/1810/11/19

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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