Effectiveness of a vision-based handle trajectory monitoring system in studying robotic suture operation

Data on surgical robots are not openly accessible, limiting further study of the operation trajectory of surgeons’ hands. Therefore, a trajectory monitoring system should be developed to examine objective indicators reflecting the characteristic parameters of operations. 20 robotic experts and 20 first-year residents without robotic experience were included in this study. A dry-lab suture task was used to acquire relevant hand performance data. Novices completed training on the simulator and then performed the task, while the expert team completed the task after warm-up. Stitching errors were measured using a visual recognition method. Videos of operations were obtained using the camera array mounted on the robot, and the hand trajectory of the surgeons was reconstructed. The stitching accuracy, robotic control parameters, balance and dexterity parameters, and operation efficiency parameters were compared. Experts had smaller center distance ( p < 0.001) and larger proximal distance between the hands ( p < 0.001) compared with novices. The path and volume ratios between the left and right hands of novices were larger than those of experts (both p < 0.001) and the total volume of the operation range of experts was smaller ( p < 0.001). The surgeon trajectory optical monitoring system is an effective and non-subjective method to distinguish skill differences. This demonstrates the potential of pan-platform use to evaluate task completion and help surgeons improve their robotic learning curve.