Collaborative Target Tracking for Laparoscopic Surgery Simulation utilizing Anticipatory Sanets

Chiu, CC; Chaczko, ZC

Collaborative Target Tracking for Laparoscopic Surgery Simulation utilizing Anticipatory Sanets

Chiu, CC Chaczko, ZC

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Publisher:: University of Technology, Sydney
Publication Type:: Conference Proceeding
Citation:: 1st Australian Conference on the Applications of Systems Engineering ACASE'12, 2012, pp. 1-2
Issue Date:: 2012-01

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Field	Value	Language
dc.contributor.author	Chiu, CC
dc.contributor.author	Chaczko, ZC
dc.contributor.editor	Chaczko, Z https://orcid.org/0000-0002-2816-7510
dc.contributor.editor	Braun, R
dc.date	2012-02-06
dc.date.accessioned	2020-05-16T14:47:59Z
dc.date.available	2020-05-16T14:47:59Z
dc.date.issued	2012-01
dc.identifier.citation	1st Australian Conference on the Applications of Systems Engineering ACASE'12, 2012, pp. 1-2
dc.identifier.isbn	978-0-9872369-4-4
dc.identifier.uri	http://hdl.handle.net/10453/140759
dc.description.abstract	Laparoscopic Surgical Simulation tools are an essential training resource for surgeons specializing in laparoscopic surgical procedures. This paper presents a Sensor-Actor Network (Sanet) training environment to simulate laparoscopic medical procedures, with the intention of using anticipatory models for target tracking and navigation. This case study implements the Belief-Desire-Intention (BDI) agent-based software reasoning approach, with neural network processes to demonstrate path trajectory planning effectively aids in the handling of laparoscopic equipment in different predefined scenarios. The immersion of the trainer in the simulation environment provides a qualitative and quantitative method of measuring the trainee's efficiency for post-analysis and feedback in laparoscopic procedures.
dc.language	en
dc.publisher	University of Technology, Sydney
dc.relation.ispartof	1st Australian Conference on the Applications of Systems Engineering ACASE'12
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Collaborative Target Tracking for Laparoscopic Surgery Simulation utilizing Anticipatory Sanets
dc.type	Conference Proceeding
utslib.location.activity	Sydney, Australia
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Architecture
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-05-16T14:47:55Z
pubs.place-of-publication	Sydney
pubs.start-date	2012-02-06
utslib.start-page	1
dc.location	Sydney

Abstract:

Laparoscopic Surgical Simulation tools are an essential training resource for surgeons specializing in laparoscopic surgical procedures. This paper presents a Sensor-Actor Network (Sanet) training environment to simulate laparoscopic medical procedures, with the intention of using anticipatory models for target tracking and navigation. This case study implements the Belief-Desire-Intention (BDI) agent-based software reasoning approach, with neural network processes to demonstrate path trajectory planning effectively aids in the handling of laparoscopic equipment in different predefined scenarios. The immersion of the trainer in the simulation environment provides a qualitative and quantitative method of measuring the trainee's efficiency for post-analysis and feedback in laparoscopic procedures.

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http://hdl.handle.net/10453/140759