short-paper

Provision of automated step-by-step procedural guidance in virtual reality surgery simulation

Authors:

Sudanthi Wijewickrema,

Gregor Kennedy,

Stephen O'LearyAuthors Info & Claims

VRST '16: Proceedings of the 22nd ACM Conference on Virtual Reality Software and Technology

Pages 69 - 72

https://doi.org/10.1145/2993369.2993397

Published: 02 November 2016 Publication History

Abstract

One of the roadblocks to the wide-spread use of virtual reality simulation as a surgical training platform is the need for expert supervision during training to ensure proper skill acquisition. To fully utilize the capacity of virtual reality in surgical training, it is imperative that the guidance process is automated. In this paper, we discuss a method of providing one aspect of performance guidance: advice on the steps of a surgery or procedural guidance. We manually segment the surgical trajectory of an expert surgeon into steps and present them one at a time to guide trainees through a surgical procedure. We show, using a randomized controlled trial, that this form of guidance is effective in moving trainee behavior towards an expert ideal.

To support practice variation and different surgical styles adopted by experts, separate guidance templates have to be generated. To enable this, we introduce a method of automatically segmenting a surgical trajectory into steps. We propose a pre-processing step that uses domain knowledge specific to our application to reduce the solution space. We show how this can be incorporated into existing trajectory segmentation methods, as well as a greedy approach that we propose. We compare this segmentation method to existing techniques and show that it is accurate and efficient.

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Cited By

Aleksic VPolitis D(2020)The Characteristics of Virtual Reality Usage in Educational Systems2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)10.1109/INISTA49547.2020.9194682(1-5)Online publication date: Aug-2020
https://doi.org/10.1109/INISTA49547.2020.9194682
Beulens AHashish YBrinkman WUmari PPuliatti SKoldewijn EHendrikx Avan Basten Jvan Merriënboer JVan der Poel HBangma CWagner C(2020)Training novice robot surgeons: Proctoring provides same results as simulator-generated guidanceJournal of Robotic Surgery10.1007/s11701-020-01118-yOnline publication date: 10-Jul-2020
https://doi.org/10.1007/s11701-020-01118-y
Lamtara JHanegbi NTalks BWijewickrema SMa XPiromchai PBailey JO’Leary S(2020)Transfer of Automated Performance Feedback Models to Different Specimens in Virtual Reality Temporal Bone SurgeryArtificial Intelligence in Education10.1007/978-3-030-52237-7_24(296-308)Online publication date: 30-Jun-2020
https://doi.org/10.1007/978-3-030-52237-7_24
Show More Cited By

Index Terms

Provision of automated step-by-step procedural guidance in virtual reality surgery simulation
1. Applied computing
  1. Education
    1. Computer-managed instruction
    2. Interactive learning environments
  2. Life and medical sciences
    1. Health care information systems

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Published In

cover image ACM Conferences

VRST '16: Proceedings of the 22nd ACM Conference on Virtual Reality Software and Technology

November 2016

363 pages

ISBN:9781450344913

DOI:10.1145/2993369

Conference Chairs:
Dieter Kranzlmüller
Leibniz Supercomputing Centre (LRZ) and Ludwig-Maximilians-Universität (LMU)
,
Gudrun Klinker
Technical University of Munich (TUM)

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 02 November 2016

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Short-paper

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VRST '16

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VRST '16: 22th ACM Symposium on Virtual Reality Software and Technology

November 2 - 4, 2016

Munich, Germany

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Overall Acceptance Rate 66 of 254 submissions, 26%

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Cited By

Aleksic VPolitis D(2020)The Characteristics of Virtual Reality Usage in Educational Systems2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)10.1109/INISTA49547.2020.9194682(1-5)Online publication date: Aug-2020
https://doi.org/10.1109/INISTA49547.2020.9194682
Beulens AHashish YBrinkman WUmari PPuliatti SKoldewijn EHendrikx Avan Basten Jvan Merriënboer JVan der Poel HBangma CWagner C(2020)Training novice robot surgeons: Proctoring provides same results as simulator-generated guidanceJournal of Robotic Surgery10.1007/s11701-020-01118-yOnline publication date: 10-Jul-2020
https://doi.org/10.1007/s11701-020-01118-y
Lamtara JHanegbi NTalks BWijewickrema SMa XPiromchai PBailey JO’Leary S(2020)Transfer of Automated Performance Feedback Models to Different Specimens in Virtual Reality Temporal Bone SurgeryArtificial Intelligence in Education10.1007/978-3-030-52237-7_24(296-308)Online publication date: 30-Jun-2020
https://doi.org/10.1007/978-3-030-52237-7_24
Williams CWijewickrema SPiromchai PO'Leary S(2019)The Effect of Practice Distribution on Skill Retention in Virtual Reality Temporal Bone Surgery Training2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)10.1109/CBMS.2019.00101(495-500)Online publication date: Jun-2019
https://doi.org/10.1109/CBMS.2019.00101
Davaris MWijewickrema SZhou YPiromchai PBailey JKennedy GO’Leary S(2019)The Importance of Automated Real-Time Performance Feedback in Virtual Reality Temporal Bone Surgery TrainingArtificial Intelligence in Education10.1007/978-3-030-23204-7_9(96-109)Online publication date: 21-Jun-2019
https://doi.org/10.1007/978-3-030-23204-7_9
Bao YWu D(2018)Real-time cutting simulation in virtual reality systems based on the measurement of porcine organsSimulation10.1177/003754971772614493:12(1073-1085)Online publication date: 30-Dec-2018
https://dl.acm.org/doi/10.1177/0037549717726144
Wijewickrema SZhou YIoannou ICopson BPiromchai PYu CBriggs RBailey JKennedy GO'Leary S(2018)Presentation of automated procedural guidance in surgical simulation: results of two randomised controlled trialsThe Journal of Laryngology & Otology10.1017/S0022215117002626132:3(257-263)Online publication date: 24-Jan-2018
https://doi.org/10.1017/S0022215117002626
Wijewickrema SMa XPiromchai PBriggs RBailey JKennedy GO’Leary S(2018)Providing Automated Real-Time Technical Feedback for Virtual Reality Based Surgical Training: Is the Simpler the Better?Artificial Intelligence in Education10.1007/978-3-319-93843-1_43(584-598)Online publication date: 20-Jun-2018
https://doi.org/10.1007/978-3-319-93843-1_43
Ma XWijewickrema SZhou SZhou YMhammedi ZO'Leary SBailey J(2017)Adversarial generation of real-time feedback with neural networks for simulation-based trainingProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3172077.3172415(3763-3769)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3172077.3172415

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