2023 Fiscal Year Final Research Report
Automatic Optimal Design of a Visual-based Stiffness Sensor and real-time Colour-coded Stiffness Map for Minimally Invasive Procedures.
| Project/Area Number |
20K14691
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 20020:Robotics and intelligent system-related
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| Research Institution | The University of Tokyo |
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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)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | Visual-based sensing / Optimal design / MIS / Medical Robotics / Remote palpation / Stiffness sensing / Topological optimization / Optimal 3D design |
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| 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.
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| Free Research Field |
Robotics
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| 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.
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