Abstract
Purpose: We are currently developing a neurosurgical robotic system that facilitates access to residual tumors and improves brain tumor removal surgical outcomes. The system combines conventional and robotic surgery allowing for a quick conversion between the procedures. This concept requires a new master console that can be positioned at the surgical bedside and be sterilized. Methods: The master console was developed using new technologies, such as a parallel mechanism and pneumatic sensors. The parallel mechanism is a purely passive 5-DOF (degrees of freedom) joystick based on the author's haptic research. The parallel mechanism enables motion input of conventional brain tumor removal surgery with a compact, intuitive interface that can be used in a conventional surgical environment. In addition, the pneumatic sensors implemented on the mechanism provide an intuitive interface and electrically isolate the tool parts from the mechanism so they can be easily sterilized. Results: The 5-DOF parallel mechanism is compact (17 cm width, 19cm depth, and 15cm height), provides a 505,050 mm and 90 workspace and is highly backdrivable (0.27N of resistance force representing the surgical motion). The evaluation tests revealed that the pneumatic sensors can properly measure the suction strength, grasping force, and hand contact. In addition, an installability test showed that the master console can be used in a conventional surgical environment. Conclusion: The proposed master console design was shown to be feasible for operative neurosurgery based on comprehensive testing. This master console is currently being tested for master-slave control with a surgical robotic system.
Original language | English |
---|---|
Pages (from-to) | 75-86 |
Number of pages | 12 |
Journal | International Journal of Computer Assisted Radiology and Surgery |
Volume | 8 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2013 |
All Science Journal Classification (ASJC) codes
- Surgery
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Health Informatics
- Computer Science Applications
- Computer Graphics and Computer-Aided Design