Classifying Situations for Collaboration among Medical Staff from Operating Room Videos

• Published in: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) pp. 2390 - 2396
• Main Authors: Hayashi, Takahiro, Kakusho, Koh, Kitahashi, Tadahiro, Matsumoto, Takashi, Sugano, Naoya
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09.10.2022
• Subjects: Anesthesia; Cameras; clustering; Collaboration; collaborative situations; Medical devices; segmentation; similarity in arrangement; Surgery; surgical operations; Three-dimensional displays; Tracking
• ISSN: 2577-1655
• DOI: 10.1109/SMC53654.2022.9945144

This article discusses the feasibility of classifying various situations for collaboration among medical staff engaged in surgery from videos taken in operating rooms. In video processing for medical use, especially for supporting surgery, many previous studies have attempted to recognize, from intraoperative videos, surgical phases constituting the workflows of specific surgical operations. However, it should also be significant to analyze, from videos obtained from observation cameras in operating rooms, how medical staff engaged in surgeries collaborate, with the aim of improving the efficiency and safety of collaboration among medical staff. The type of collaborative situations that occur are not predetermined but rather depend on actual behavior of medical staff during surgeries. Therefore, this study attempts to segment videos of surgical operating rooms into different collaborative situations by clustering the video frames based on similarities in the arrangements of medical staff. The arrangements are represented by the distributions of medical staff in the operating rooms as well as their observed postures observed in the video frames. In the results of our experiment with the video of a real surgery, some meaningful clusters of collaborative situations for medical staff could be obtained.