Evaluation of robotic minimally invasive surgical skills using motion studies

Robotic Minimally Invasive Surgery, and the engendered computer-integration, offers unique opportunities for quantitative computer-based surgical-performance evaluation. In this work, we examine extension of traditional manipulative skill assessment, having deep roots in performance evaluation in manufacturing industries, for applicability to robotic surgical skill evaluation. This method relies on: defining task-level segmentation of modular sub-tasks/micro-motions called ‘Therbligs’ that can be combined to perform a given task; and analyzing intra- and inter-user performance variance by studying surgeons’ performance over each ‘Therbligs’. Any of the performance metrics of macro-motions—from motion-economy, tool motion measurements to handed-symmetry—can now be extended over the micro-motion temporal segments. Evaluation studies were based on video recordings of surgical tasks in two settings: first, we examined performance of two representative manipulation exercises (peg board and pick-and-place) on a da Vinci surgical SKILLS simulator. This affords a relatively-controlled and standardized test-scenarios for surgeons with varied experience-levels. Second, task-sequences from real surgical videos were analyzed with a list of predefined ‘Therbligs’ in order to investigate its overall usefulness.