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Designing a Novel VR Simulator for Core Laparoscopic Skills and Assessing Its Construct Validity via Machine Learning

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Advances in Information and Communication (FICC 2024)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 919))

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Abstract

We introduce an innovative and highly portable VR simulator, SECMA, designed to enhance minimally invasive surgery (MIS) training through immersive simulations of basic laparoscopy techniques. This simulator transforms the Oculus Quest headset into an educational tool with four key components: (1) a mechanical interface emulating surgical instruments, (2) virtual scenarios replicating operating rooms, (3) a real-time data capture system, and (4) machine learning tools to differentiate between the proficiency levels of experienced surgeons and novices. SECMA underwent construct validation through iterative simulations of two distinct virtual scenarios: (1) Coordination and (2) Grasp and Transport. The study cohort consisted of 21 individuals, stratified into eleven novices with limited experience and ten experts, each with over a hundred endoscopic procedures. A set of metrics, including activity elapsed time, error scores, right-hand speed, and pathway length, was systematically collected for subsequent in-depth analysis. Data, automatically acquired by the simulator, were subjected to statistical analyses (hypothesis testing, linear regressions, ANOVA, PCA) and harnessed for machine learning classification (using LDA, GLM, KNN, SVM, XGBOOST, RF). The experiment outcomes revealed that experts outperformed novices across all assessed parameters. The discernible discrepancy between the two cohorts underscores SECMA's ability to discriminate between the skill levels of experienced surgeons and novices, yielding substantial evidence of its construct validity. The discussion highlights the potential of devices like SECMA, which repurpose VR headsets, to revolutionize virtual education across various domains of expertise. By providing an immersive and adaptable learning experience, SECMA holds promise as a paradigm-shifting tool capable of reshaping MIS training.

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Acknowledgment

We would like to express our gratitude to the leadership of the Faculty of Engineering at the Universidad del Desarrollo for their support of this research from its inception. Additionally, we extend our thanks to the Surgical Skills Center of Chile for their recommendations to enhance the simulator.

We extend our appreciation to the Corporation for the Development of Production (CORFO) for funding the project in its early stages, and particularly to the National Agency for Research and Development of Chile (ANID) for enabling the continuity of the SECMA project. Their support is made possible through the Technological Research Contest IDeA 2023, with project code IT23I0018.

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Authors and Affiliations

  1. Engineering Faculty, Universidad del Desarrollo, Santiago, Chile

    José Ignacio Guzmán Montoto, Mauricio Herrera & Camilo Rodríguez Beltrán

  2. Medical School, Universidad de Chile, Santiago, Chile

    Boris Marinkovic Gomez

Authors
  1. José Ignacio Guzmán Montoto
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  2. Mauricio Herrera
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  3. Camilo Rodríguez Beltrán
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  4. Boris Marinkovic Gomez
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Corresponding author

Correspondence to José Ignacio Guzmán Montoto .

Editor information

Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

Appendix A

Appendix A

Table 7. Table comparing SECMA with other MIS Simulators(1)
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Montoto, J.I.G., Herrera, M., Beltrán, C.R., Gomez, B.M. (2024). Designing a Novel VR Simulator for Core Laparoscopic Skills and Assessing Its Construct Validity via Machine Learning. In: Arai, K. (eds) Advances in Information and Communication. FICC 2024. Lecture Notes in Networks and Systems, vol 919. Springer, Cham. https://doi.org/10.1007/978-3-031-53960-2_44

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