Objective: Virtual Reality (VR) simulators represent a remarkable educational opportunity in order to acquire and refine surgical practical skills. Nevertheless, there exists no consensus regarding a standard curriculum of simulation-based training. This study introduces an automatic, adaptive curriculum where the training session is real-time scheduled on the basis of the trainee's performances. Methods: An experimental study using the master console of the da Vinci Research Kit (Intuitive Surgical Inc., Sunnyvale, US) was carried out to test this approach. Tasks involving fundamental skills of robotic surgery were designed and simulated in VR. Twelve participants without medical background along with twelve medical residents were randomly and equally divided into two groups: a control group, self-managing the training session, and an experimental group, undergoing the proposed adaptive training. Results: The performances of the experimental users were significantly better with respect to the ones of the control group after training (non-medical: p < 0.01; medical: p = 0.02). This trend was analogous in the non-medical and medical populations and no significant difference was identified between these two classes (even in the baseline assessment). Conclusion: The analysis of the learning of the involved surgical skills highlighted how the proposed adaptive training managed to better identify and compensate for the trainee's gaps. The absence of initial difference between the non-medical and medical users underlines that robotic surgical devices require specific training before clinical practice. Significance: This feasibility study could pave the way towards the improvement of simulation-based training curricula.

Skill-Oriented and Performance-Driven Adaptive Curricula for Training in Robot-Assisted Surgery Using Simulators: A Feasibility Study

Mariani A.;De Momi E.
2021-01-01

Abstract

Objective: Virtual Reality (VR) simulators represent a remarkable educational opportunity in order to acquire and refine surgical practical skills. Nevertheless, there exists no consensus regarding a standard curriculum of simulation-based training. This study introduces an automatic, adaptive curriculum where the training session is real-time scheduled on the basis of the trainee's performances. Methods: An experimental study using the master console of the da Vinci Research Kit (Intuitive Surgical Inc., Sunnyvale, US) was carried out to test this approach. Tasks involving fundamental skills of robotic surgery were designed and simulated in VR. Twelve participants without medical background along with twelve medical residents were randomly and equally divided into two groups: a control group, self-managing the training session, and an experimental group, undergoing the proposed adaptive training. Results: The performances of the experimental users were significantly better with respect to the ones of the control group after training (non-medical: p < 0.01; medical: p = 0.02). This trend was analogous in the non-medical and medical populations and no significant difference was identified between these two classes (even in the baseline assessment). Conclusion: The analysis of the learning of the involved surgical skills highlighted how the proposed adaptive training managed to better identify and compensate for the trainee's gaps. The absence of initial difference between the non-medical and medical users underlines that robotic surgical devices require specific training before clinical practice. Significance: This feasibility study could pave the way towards the improvement of simulation-based training curricula.
2021
adaptive logics
robot-assisted surgery
skill assessment
training and motor learning
Virtual reality simulators
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1168380
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