Simulation-based surgical training systems in laparoscopic surgery: a current review

Autor: Minsik Hong, Jerzy W. Rozenblit, Allan J. Hamilton
Rok vydání: 2020
Předmět:
Zdroj: Virtual Reality. 25:491-510
ISSN: 1434-9957
1359-4338
DOI: 10.1007/s10055-020-00469-z
Popis: Simulation-based training has been widely used in medical education. More specifically, various systems for minimally invasive surgery training have been proposed in the past two decades. The aim of this article is to review and summarize the existing simulation-based training systems for laparoscopic surgery in terms of their technical realizations. Forty-three training systems were found and analyzed. These training systems generally consist of training tasks, a visualization interface, and an instrument interface. Three different approaches—physical, virtual, and augmented reality—to implement visualization interfaces are discussed first. Then, haptic feedback, performance evaluation, and guidance methods are summarized. Portable devices to enable at-home training and instrument tracking technologies to support visualization, evaluation, and guidance are also presented. Based on survey of the relevant literature, we propose several recommendations to design the next-generation training systems in laparoscopic surgery. Novel guidance and assessment schemes with augmented reality visualization are recommended to design an intelligent surgical training simulator. This intelligent simulator enhances the training procedure and ultimately improves the patient safety.
Databáze: OpenAIRE