Akinori Hidaka
Papers
1
Total Citations
2
H-Index
1
About
Akinori Hidaka’s research lies at the intersection of computer vision, robotics, and surgical automation, with a primary focus on enabling intelligent systems to understand and assist in complex medical procedures. His most cited work introduces a convolutional neural network that leverages temporal pose features for surgical procedure recognition, a critical component of the scrub nurse robot (SNR) system developed by Miyawaki and colleagues. This system aims to address the severe shortage of scrub nurses by automating their supportive roles during surgery. Hidaka’s contribution—designing a model that interprets sequential human motion to identify surgical steps—directly advances the SNR’s ability to anticipate and respond to a surgeon’s needs in real time. While his citation count is still growing, the practical impact of his work is significant, bridging deep learning with real-world clinical robotics. By focusing on temporal dynamics and pose estimation, Hidaka is helping to shape a future where autonomous assistants can seamlessly collaborate with surgical teams, improving efficiency and patient outcomes.
Research Focus
Key Achievements
Top Papers
- 1