Accuracy improvement of a neurosurgical robot system

Abstract

Neurosurgery was the first field of application for robots in interventional medicine 20 years ago, and since then dozens of research projects have been focusing on brain and spine surgery, differently addressing the challenges of accuracy and effectiveness. We have developed a cooperatively-controlled system to assist with skull base drilling, to improve the safety and quality of neurosurgery while reducing the operating time. This paper presents the entire system, the preliminary results of phantom and cadaver tests and our efforts to improve the accuracy of the components. The residual error of NeuroMate robot calibration was reduced by 24%, while decreasing the noise of the integrated StealthStation navigation system by 53%. An effective optical tracking based patient motion compensation method has been implemented and tested. The results verify the effectiveness of the system and allow for further research. We hope that by improving the accuracy and safety, we can one day introduce this system into clinical use.