Objective assessment of minimally invasive surgical skills

Minimally invasive surgery (MIS) is known to be a difficult procedure to master due to its complexity, compared to traditional open surgery. Therefore, an objective and quantitative assessment tool is highly required in MIS, which can be used for determining surgeon's skills, evaluating educational programs and providing subjects with unbiased feedback. The goal of this paper is to review various assessment methods, summarize capabilities of the methods, and suggest future possible improvements. Specifically, this paper categorize existing methods into two groups: the first and the most well known group focuses on the analysis of surgical motions, and the other group uses force and torque as a key metric. Specifically, motion analysis includes tracking the body, tool, or hand motions of a surgeon, either from teleoperated robotic systems or surgical simulators using different sensors like wireless or electromagnetic motion tracking sensors, videoglove- based input devices, optical tracking system, or magnetic tracking technologies. Sometimes data explored form this method is synchronized with eye-gaze data (what a surgeon looks at while operating), or videographic data. Using motion analysis actually the number of movements, rate of movements, total path length, movement variability, time taken to complete the operation, average or peak velocity are considered for assessing surgical skills. On the other hand, the methods in the second group assess the skills based on force and toque data that surgeons apply through surgical instruments. More specifically, these methods use different kind of sensors placed on the grasper. Different force and torque measurement systems, hidden-Markov-model-based analysis, simulated models with criteria, and Virtual reality have been developed, allowing for the quantification of the performance of surgeons. Although, each method has its own advantageous, and according to the kind of surgical task and evaluation, these methods can be used successfully to assess surgical skills, to provide predictive validity for each of these methods more study is needed. Also, future works should improve the efficiency of each method and move toward automated, lowcost and real time assessment methods.