In response to the escalating demand for skilled surgeons proficient in robotic-assisted pro cedures, this study addresses the need for comprehensive training solutions. The surge in surgical robotics necessitates a proficient workforce capable of harnessing the benefits of Robot-Assisted Minimally Invasive Surgery safely and effectively. Contemporary training methodologies leverage Virtual Reality and simulated environments to impart a scalable, cost-effective, and thorough acquisition of surgical robotic skills. This work focuses on the development and validation of an adaptive surgical simulator for the da Vinci® surgical robot, specifically tailored for training in a Virtual Reality environment. The simulator includes five tasks, each designed to enhance specific robotic surgical skills. Notably, the simulator incorporates an adaptive algorithm that dynami cally adjusts the difficulty level of tasks based on the trainee’s performance, ensuring a customized and progressively challenging learning experience. Results from the experimental study indicate increasing performance trends in both adap tive and control groups during training. On the final test day, the adaptive group demon strates consistently high performance, outperforming the control group. The study emphasizes the adaptive simulator’s effectiveness in accelerating skill acquisi tion. The overall findings support the integration of adaptive training methods in surgical education. The adaptive simulator applied in a VR setting not only enhances learning outcomes but also provides a scalable, safe, and efficient approach to training future sur geons. This research contributes significantly to the field of surgical education and training, show casing the potential of adaptive simulators in optimizing the learning curve for robotic assisted surgical procedures. The study’s outcomes pave the way for future developments in medical training technologies, promising a transformative impact on surgical education and practice.
Data la crescente domanda di chirurghi esperti nelle procedure assistite da robot, questo studio affronta la necessità di soluzioni di formazione. L’incremento nella robotica chirur gica richiede una manodopera competente, in grado di sfruttare in modo sicuro ed efficace i vantaggi della Chirurgia Mininvasiva Robotica Assistita. Le metodologie di formazione attuali fanno uso di Realtà Virtuale e ambienti simulati per fornire un acquisizione scal abile, economica e approfondita delle competenze in robotica chirurgica. Questo lavoro si concentra sullo sviluppo e la convalida di un simulatore chirurgico adat tativo per il robot chirurgico da Vinci®, progettato per la formazione in un ambiente di Realtà Virtuale. Il simulatore include cinque esercizi, ognuno ideato per migliorare com petenze specifiche in chirurgia robotica. Il simulatore incorpora un algoritmo adattativo che regola dinamicamente il livello di difficoltà degli esercizi in base alle prestazioni del trainee, garantendo un apprendimento personalizzato e progressivamente stimolante. I risultati dello studio sperimentale indicano una curva crescente delle performance sia nel gruppo adattativo che in quello di controllo durante la formazione. Nel giorno del test finale, il gruppo adattativo mostra prestazioni costantemente elevate, superando il gruppo di controllo. Lo studio sottolinea l’efficacia del simulatore nell’accelerare l’acquisizione di competenze. Le conclusioni supportano l’integrazione di metodi di formazione adattativa nell’educazione chirurgica. Il simulatore adattativo applicato in un contesto VR non solo migliora i risul tati dell’apprendimento, ma fornisce anche un approccio scalabile, sicuro ed efficiente per la formazione dei futuri chirurghi. Questa ricerca contribuisce significativamente al campo dell’educazione e della formazione chirurgica, mostrando il potenziale dei simulatori adattativi nell’ottimizzare la curva di apprendimento per le procedure chirurgiche assistite da robot. I risultati dello studio aprono la strada a futuri sviluppi nelle tecnologie di formazione medica, promettendo un impatto trasformativo sull’educazione e sulla pratica chirurgica.
Performance-Driven Tasks with Adaptive Difficulty for Surgical Robotics Training on a daVinci Robot
SUN, XIANYI FEDERICA
2022/2023
Abstract
In response to the escalating demand for skilled surgeons proficient in robotic-assisted pro cedures, this study addresses the need for comprehensive training solutions. The surge in surgical robotics necessitates a proficient workforce capable of harnessing the benefits of Robot-Assisted Minimally Invasive Surgery safely and effectively. Contemporary training methodologies leverage Virtual Reality and simulated environments to impart a scalable, cost-effective, and thorough acquisition of surgical robotic skills. This work focuses on the development and validation of an adaptive surgical simulator for the da Vinci® surgical robot, specifically tailored for training in a Virtual Reality environment. The simulator includes five tasks, each designed to enhance specific robotic surgical skills. Notably, the simulator incorporates an adaptive algorithm that dynami cally adjusts the difficulty level of tasks based on the trainee’s performance, ensuring a customized and progressively challenging learning experience. Results from the experimental study indicate increasing performance trends in both adap tive and control groups during training. On the final test day, the adaptive group demon strates consistently high performance, outperforming the control group. The study emphasizes the adaptive simulator’s effectiveness in accelerating skill acquisi tion. The overall findings support the integration of adaptive training methods in surgical education. The adaptive simulator applied in a VR setting not only enhances learning outcomes but also provides a scalable, safe, and efficient approach to training future sur geons. This research contributes significantly to the field of surgical education and training, show casing the potential of adaptive simulators in optimizing the learning curve for robotic assisted surgical procedures. The study’s outcomes pave the way for future developments in medical training technologies, promising a transformative impact on surgical education and practice.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/215779