Project/Area Number |
20K14691
|
Research Category |
Grant-in-Aid for Early-Career Scientists
|
Allocation Type | Multi-year Fund |
Review Section |
Basic Section 20020:Robotics and intelligent system-related
|
Research Institution | The University of Tokyo |
Principal Investigator |
Faragasso Angela 東京大学, 大学院工学系研究科(工学部), 特任助教 (80847070)
|
Project Period (FY) |
2020-04-01 – 2024-03-31
|
Project Status |
Completed (Fiscal Year 2023)
|
Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2021: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2020: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
|
Keywords | Visual-based sensing / Optimal design / MIS / Medical Robotics / Remote palpation / Stiffness sensing / Topological optimization / Optimal 3D design / Visual based sensing / Remote Palpation / Topological Optimization / Stiffness Sensing / Real-time Stiffness Map / Stiffness map / Stiffness Sensor / Laparoscopic Surgery / Optimal 3D Design |
Outline of Research at the Start |
The aim of this research is to create a real-time stiffness map for minimally invasive procedures by developing an optimal task-specific visual-based stiffness sensor, to be embedded at the tip of the endoscopic camera, and used to model the nonlinear behaviour characterizing anatomical surfaces.
|
Outline of Final Research Achievements |
This research developed a sensor to enhance the safety and accuracy of minimally invasive surgeries. The sensor was integrated with a lightweight robot, allowing for remote operation and real-time feedback on tissue stiffness. Control and visualization were enhanced using the Meta Quest 3.
Key achievements include the development of a navigation algorithm for precise remote control of the robot. The information collected can be used to create a real-time color-coded stiffness map, improving the precision and safety of surgeries.
|
Academic Significance and Societal Importance of the Research Achievements |
This technology enhances surgical procedures by providing real-time stiffness information during minimally invasive surgeries, improving the quality of outcomes. By increasing surgical precision and safety, it contributes to better patient recovery and overall healthcare quality.
|