Efficiency assessment of nanosecond laser robotic maxillofacial area surgery in experiment

Abstract

The aim of the study was to study the root mean square deviation from a given trajectory while performing standard surgical incisions using laser radiation with a tip built into the manipulating robot relative to a surgeon’s arm using a manual training system. Materials and Methods. We used a nanosecond laser device with unique radiation characteristics and a manipulating robot, which is a hinged seven-link mechanism with a sequential kinematic structure conjugated by a prototype of the working element holding the holder of the optical fiber of the medical laser on the flange of the 6-degree manipulator. The coordinates of points were measured by typical trajectories (linear, curve, festoon) taking into account functional movements of the medical instrument in manual procedures and when being moved by the robot using a laser coordinate measuring device with its reflector being fixed on the prototype of the working element. Results. The root mean square deviation in manual movements in a linear trajectory was found to be 11 times greater (p≤0.05) than when being moved by the robot, and 5 times greater (p≤0.05) in a curve trajectory. The mean value of all root mean square deviations for each of the small circles on the festoon trajectory for manual movements was threefold (p≤0.05) to when being moved by the robot. The standard deviation from the straight line equidistant from all the centers of small circles in manual movements was fourfold (p≤0.05) compared to that in robot movements. The mean value of root mean square deviation in various trajectories (linear, curve, festoon) with manual movement was 3.3 times greater than when being moved by the robot. Conclusion. The results of the study suggest that the use of robotic laser systems in medicine, in particular, the one developed by us for the maxillofacial region, makes it possible to significantly improve the accuracy of medical laser movements, which is of prime importance in complex trajectories.