4.6 Article

A novel augmented reality simulator for skills assessment in minimal invasive surgery

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SPRINGER
DOI: 10.1007/s00464-014-3930-y

Keywords

Augmented reality; Laparoscopy; Simulation; Performance assessment

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Over the past decade, simulation-based training has come to the foreground as an efficient method for training and assessment of surgical skills in minimal invasive surgery. Box-trainers and virtual reality (VR) simulators have been introduced in the teaching curricula and have substituted to some extent the traditional model of training based on animals or cadavers. Augmented reality (AR) is a new technology that allows blending of VR elements and real objects within a real-world scene. In this paper, we present a novel AR simulator for assessment of basic laparoscopic skills. The components of the proposed system include: a box-trainer, a camera and a set of laparoscopic tools equipped with custom-made sensors that allow interaction with VR training elements. Three AR tasks were developed, focusing on basic skills such as perception of depth of field, hand-eye coordination and bimanual operation. The construct validity of the system was evaluated via a comparison between two experience groups: novices with no experience in laparoscopic surgery and experienced surgeons. The observed metrics included task execution time, tool pathlength and two task-specific errors. The study also included a feedback questionnaire requiring participants to evaluate the face-validity of the system. Between-group comparison demonstrated highly significant differences (< 0.01) in all performance metrics and tasks denoting the simulator's construct validity. Qualitative analysis on the instruments' trajectories highlighted differences between novices and experts regarding smoothness and economy of motion. Subjects' ratings on the feedback questionnaire highlighted the face-validity of the training system. The results highlight the potential of the proposed simulator to discriminate groups with different expertise providing a proof of concept for the potential use of AR as a core technology for laparoscopic simulation training.

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