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Authors: Jodavid Ferreira 1 ; 2 ; Arthur Lopes 2 ; Liliane S. Machado 2 ; 3 and Ronei M. Moraes 2 ; 4

Affiliations: 1 Graduate Program in Decision Models and Health, Federal University of Paraíba, João Pessoa, Paraíba, Brazil ; 2 Laboratory of Technologies for Virtual Teaching and Statistics, Federal University of Paraíba, João Pessoa, Paraíba, Brazil ; 3 Departament of Informatics, Federal University of Paraíba, João Pessoa, Paraíba, Brazil ; 4 Departament of Statistics, Federal University of Paraíba, João Pessoa, Paraíba, Brazil

Keyword(s): Fuzzy Geometric Naive Bayes, Geometric Distribution, User’s Assessment, Virtual Reality.

Abstract: Computational intelligence-based assessment systems have been proposed for implementation in virtual reality (VR) simulators to enhance technical proficiency in secure environments. Traditional training methods in healthcare, such as live subjects, cadavers, or mannequins, have limitations in reflecting realistic characteristics and deteriorate over time. Virtual reality-based assessment systems offer the advantage of check users skills in realistic and immersive training experiences, providing feedback at the end of the training. This paper presents a novel approach to assessment using a Single-User Assessment System (SUAS) that incorporates a Fuzzy Geometric Naive Bayes Network. The proposed method utilizes geometric distribution to model the fuzzy boundaries and assess the performance of gynecological examinations in a virtual reality simulator. The study evaluates the effectiveness of the proposed SUAS by comparing it with three other assessment methods. The results demonstrate t he superior performance of the proposed method in accurately evaluating user performance in the simulated gynecological examinations. (More)

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Paper citation in several formats:
Ferreira, J.; Lopes, A.; S. Machado, L. and M. Moraes, R. (2023). A Novel Fuzzy Geometric Naive Bayes Network for Online Skills Assessment in Training Based on Virtual Reality. In Proceedings of the 15th International Joint Conference on Computational Intelligence - FCTA; ISBN 978-989-758-674-3; ISSN 2184-3236, SciTePress, pages 395-401. DOI: 10.5220/0012211000003595

@conference{fcta23,
author={Jodavid Ferreira. and Arthur Lopes. and Liliane {S. Machado}. and Ronei {M. Moraes}.},
title={A Novel Fuzzy Geometric Naive Bayes Network for Online Skills Assessment in Training Based on Virtual Reality},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - FCTA},
year={2023},
pages={395-401},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012211000003595},
isbn={978-989-758-674-3},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - FCTA
TI - A Novel Fuzzy Geometric Naive Bayes Network for Online Skills Assessment in Training Based on Virtual Reality
SN - 978-989-758-674-3
IS - 2184-3236
AU - Ferreira, J.
AU - Lopes, A.
AU - S. Machado, L.
AU - M. Moraes, R.
PY - 2023
SP - 395
EP - 401
DO - 10.5220/0012211000003595
PB - SciTePress