Global versus local kinematic skills assessment on robotic assisted hysterectomies

Abstract

Surgical skills assessment is a crucial step to help understanding surgical expertise and to provide technical knowledge to beginners. Scores, such as GOALS [1], have been designed to assess surgical skills. However, these scores are subjective and need experts to compute them. With the advent of robotic surgery, it is possible to compute Automated Performance Metrics (APMs) based on the motion of robotic arms to assess surgical skills. Several studies have demonstrated statistically significant differences between APMs from different levels of expertise [2], [3]. The majority of these studies performed a global analysis, i.e., studying the surgical procedure or training task as a whole. By using the Surgical Process Model (SPM) methodology [4], it is possible to describe the surgery at different levels of granularity and break it down into a sequence of elements. Riffaud et al. [5], decomposed Lumbar Disc herniation surgery by phases and demonstrated that the main expertise differences in terms of duration are due to specific phases or actions. In this paper, we will combine SPM and APMs to study global and local kinematic skills during robotic-assisted hysterectomies.