Surgical workflow monitoring based on trajectory data mining

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

doi:10.1007/978-3-642-25655-4_27

Surgical workflow monitoring based on trajectory data mining

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

17 Citations (Scopus)

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.

Original language	English
Title of host publication	New Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers
Pages	283-291
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-25655-4_27
Publication status	Published - 2011
Externally published	Yes
Event	2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010 - Tokyo, Japan Duration: 2010 Nov 18 → 2010 Nov 19

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6797 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010
Country/Territory	Japan
City	Tokyo
Period	10/11/18 → 10/11/19

Keywords

Surgical Management
Surgical Workflow
Trajectory Analysis

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-25655-4_27

Cite this

Nara, A., Izumi, K., Iseki, H., Suzuki, T., Nambu, K., & Sakurai, Y. (2011). Surgical workflow monitoring based on trajectory data mining. In New Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers (pp. 283-291). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6797 LNAI). https://doi.org/10.1007/978-3-642-25655-4_27

Surgical workflow monitoring based on trajectory data mining. / Nara, Atsushi; Izumi, Kiyoshi; Iseki, Hiroshi et al.
New Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers. 2011. p. 283-291 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6797 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nara, A, Izumi, K, Iseki, H, Suzuki, T, Nambu, K & Sakurai, Y 2011, Surgical workflow monitoring based on trajectory data mining. in New Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6797 LNAI, pp. 283-291, 2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010, Tokyo, Japan, 10/11/18. https://doi.org/10.1007/978-3-642-25655-4_27

Nara A, Izumi K, Iseki H, Suzuki T, Nambu K, Sakurai Y. Surgical workflow monitoring based on trajectory data mining. In New Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers. 2011. p. 283-291. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-25655-4_27

Nara, Atsushi ; Izumi, Kiyoshi ; Iseki, Hiroshi et al. / Surgical workflow monitoring based on trajectory data mining. New Frontiers in Artificial Intelligence - JSAI-isAI 2010 Workshops, LENLS, JURISIN, AMBN, ISS, Revised Selected Papers. 2011. pp. 283-291 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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 Management, Surgical Workflow, Trajectory Analysis",

author = "Atsushi Nara and Kiyoshi Izumi and Hiroshi Iseki and Takashi Suzuki and Kyojiro Nambu and Yasuo Sakurai",

note = "Funding Information: Open Access Ver?ffentlichung erm?glicht und organisiert durch Projekt DEAL.; 2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010 ; Conference date: 18-11-2010 Through 19-11-2010",

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AU - Nara, Atsushi

AU - Izumi, Kiyoshi

AU - Iseki, Hiroshi

AU - Suzuki, Takashi

AU - Nambu, Kyojiro

AU - Sakurai, Yasuo

N1 - Funding Information: Open Access Ver?ffentlichung erm?glicht und organisiert durch Projekt DEAL.

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

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Surgical workflow monitoring based on trajectory data mining

Abstract

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Conference

Keywords

ASJC Scopus subject areas

Access to Document

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