通过计算机视觉评估手术室的团队态势感知。

Roger D Dias, Lauren R Kennedy-Metz, Steven J Yule, Matthew Gombolay, Marco A Zenati
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引用次数: 1

摘要

个人和团队层面的态势感知(SA)在手术室(OR)中都起着至关重要的作用。在切开前暂停期间,整个手术室团队一起部署手术安全检查表(SSC)。在世界范围内,SSC的实施已被证明可以减少手术患者的术中并发症和死亡率。在这项研究中,我们研究了在手术视频中应用计算机视觉分析来提取团队运动指标的可行性,这些指标可以在切口前暂停期间区分SA良好的团队和SA较差的团队。我们使用经过验证的基于观察的工具来评估SA,并使用计算机视觉软件来测量手术室中的身体位置和运动模式。我们的研究结果表明,通过现成的手术室摄像机提取外科团队运动指标是可行的。熵作为团队组织水平的度量能够区分SA好的和差的外科团队。这些发现证实了现有的研究表明,基于计算机视觉的运动指标有潜力整合传统的基于观察的手术室性能评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing Team Situational Awareness in the Operating Room via Computer Vision.

Situational awareness (SA) at both individual and team levels, plays a critical role in the operating room (OR). During the pre-incision time-out, the entire OR team comes together to deploy the surgical safety checklist (SSC). Worldwide, the implementation of the SSC has been shown to reduce intraoperative complications and mortality among surgical patients. In this study, we investigated the feasibility of applying computer vision analysis on surgical videos to extract team motion metrics that could differentiate teams with good SA from those with poor SA during the pre-incision time-out. We used a validated observation-based tool to assess SA, and a computer vision software to measure body position and motion patterns in the OR. Our findings showed that it is feasible to extract surgical team motion metrics captured via off-the-shelf OR cameras. Entropy as a measure of the level of team organization was able to distinguish surgical teams with good and poor SA. These findings corroborate existing studies showing that computer vision-based motion metrics have the potential to integrate traditional observation-based performance assessments in the OR.

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