Abstract
Abstract
Purpose
The expanded endoscopic endonasal approach, a representative example of keyhole brain surgery, allows access to the pituitary gland and surrounding areas through the nasal and sphenoid cavities. Manipulating rigid instruments through these constrained spaces makes this approach technically challenging, and thus, a handheld robotic instrument could expand the surgeon’s capabilities. In this study, we present an intuitive handle prototype for such a robotic instrument.
Methods
We have designed and fabricated a surgical instrument handle prototype that maps the surgeon’s wrist directly to the robot joints. To alleviate the surgeon’s wrist of any excessive strain and fatigue, the tool is mounted on the surgeon’s forearm, making it parallel with the instrument’s shaft. To evaluate the handle’s performance and limitations, we constructed a surgical task simulator and compared our novel handle with a standard neurosurgical tool, with the tasks being performed by a consultant neurosurgeon.
Results
While using the proposed handle, the surgeon’s average success rate was $$80\%$$
80
%
, compared to $$41\%$$
41
%
when using a conventional tool. Additionally, the surgeon’s body posture while using the suggested prototype was deemed acceptable by the Rapid Upper Limb Assessment ergonomic survey, while early results indicate the absence of a learning curve.
Conclusions
Based on these preliminary results, the proposed handle prototype could offer an improvement over current neurosurgical tools and procedural ergonomics. By redirecting forces applied during the procedure to the forearm of the surgeon, and allowing for intuitive surgeon wrist to robot-joints movement mapping without compromising the robotic end effector’s expanded workspace, we believe that this handle could prove a substantial step toward improved neurosurgical instrumentation.
Funder
Wellcome/EPSRC Centre for Interventional and Surgical Sciences
Engineering and Physical Sciences Research Council
H2020 Future and Emerging Technologies
Royal Academy of Engineering
National Brain Appeal
National Institute for Health Research, UCLH-Biomedical Research Centre
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
Cited by
11 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献