An Automatic Multi-metrics-based Evaluating Model of Surgeon’s Operating Performance for Interventional Surgical Robotic System

A quantitative operation performance assessment is essential for establishing surgeons’ learning curve and improving the techniques for operating surgical robots in percutaneous coronary intervention (PCI). Most of the existing evaluation methods only consider the influence of catheter and guidewire’s tip, and they are almost not automatic. However, the overall shape of guidewire and catheter have a great impact on surgical performance. In this study, an automatic evaluation model is introduced to deal with the above issue. Firstly, guidewire’s offset, velocity and contact force are considered in this model. Additionally, the guidewire’s offset and velocity are the features extracted from the video sequence, and the contact force is the feature obtained by the force sensor. Secondly, analytic hierarchy process (AHP) is used to establish automatic evaluation model with ability of quantitative assessment based on the above three metrics. Lastly, the proposed model was evaluated by the experiments through a given task, which shows that the proposed model can train and improve the operation skills for interventional surgical robotic system.