Shota Tsuyuki
Papers
1
Total Citations
2
H-Index
1
About
Shota Tsuyuki is a researcher at the forefront of surgical robotics and human-robot interaction, with a primary focus on enabling autonomous systems to understand and assist in complex medical procedures. His key research areas include surgical procedure recognition, temporal pose analysis, and the development of intelligent scrub nurse robots. Tsuyuki’s major contribution lies in advancing convolutional neural network architectures that leverage temporal pose features to allow robotic systems to recognize distinct surgical phases in real time. This work directly addresses the critical shortage of skilled scrub nurses by empowering robotic assistants to anticipate surgeon needs and provide timely instrument support. His most cited paper, "Convolutional Neural Network based on Temporal Pose Features for Surgical Procedure Recognition" (2021, 2 citations), lays foundational groundwork for integrating motion-based understanding into surgical workflows. While still early in his career, Tsuyuki’s research represents a vital step toward safer, more efficient operating rooms where robots seamlessly collaborate with human surgical teams. His ongoing efforts promise to reshape perioperative care through context-aware automation.
Research Focus
Key Achievements
Top Papers
- 1