Yusuke Yokoyama
Papers
1
Total Citations
11
H-Index
1
About
Yusuke Yokoyama is a researcher at the forefront of robotic-assisted orthopedic surgery, with a primary focus on enhancing precision and safety in total knee arthroplasty. His key contributions lie in the development of intelligent control systems for surgical robotics, particularly in optimizing cutting feed rates during bone preparation. In his most cited work, "Optimal control of cutting feed rate in the robotic milling for total knee arthroplasty" (2010, 11 citations), Yokoyama introduced a novel approach that adjusts the robotic milling speed based on bone tissue hardness predicted from preoperative medical images. This innovation significantly reduces cutting forces, thereby minimizing bone displacement and improving implant alignment accuracy. Although his citation count is modest, his work represents a critical step toward adaptive, image-guided robotic surgery—a field with growing clinical importance. Yokoyama’s research bridges mechanical engineering, medical imaging, and robotics, offering a practical solution to one of the key challenges in joint replacement: achieving consistent, minimally invasive bone cuts. His contributions are particularly valuable for students and researchers interested in the intersection of robotics and orthopedics, demonstrating how control theory can be applied to enhance surgical outcomes.
Research Focus
Key Achievements
Top Papers
- 1