Objective: Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; however, the importance and effect of the different treatments are not fully explored. The available data are collected in Tanzania, during newborn resuscitation, for analysis of the resuscitation activities and the response of the newborn. An important step in the analysis is to create activity timelines of the episodes, where activities include ventilation, suction, stimulation, etc. Methods: The available recordings are noisy real-world videos with large variations. We propose a two-step process in order to detect activities possibly overlapping in time. The first step is to detect and track the relevant objects, such as bag-mask resuscitator, heart rate sensors, etc., and the second step is to use this information to recognize the resuscitation activities. The topic of this paper is the first step, and the object detection and tracking are based on convolutional neural networks followed by post processing. Results: The performance of the object detection during activities were 96.97% (ventilations), 100% (attaching/removing heart rate sensor), and 75% (suction) on a test set of 20 videos. The system also estimate the number of health care providers present with a performance of 71.16%. Conclusion: The proposed object detection and tracking system provides promising results in noisy newborn resuscitation videos. Significance: This is the first step in a thorough analysis of newborn resuscitation episodes, which could provide important insight about the importance and effect of different newborn resuscitation activities.

中文翻译：

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新生儿复苏活动中的目标检测

目的：出生窒息是资源贫乏国家的主要新生儿死亡率问题。国际指南提供了治疗建议；但是，尚未充分探讨不同治疗方法的重要性和效果。在坦桑尼亚，新生儿复苏期间收集了可用的数据，用于分析复苏活动和新生儿的反应。分析中的重要步骤是创建情节的活动时间表，其中活动包括通气，吸气，刺激等。方法：可用的记录是嘈杂的真实世界视频，变化很大。为了提出可能在时间上重叠的活动，我们提出了一个两步过程。第一步是检测和跟踪相关物体，例如袋罩复苏器，心率传感器等，第二步是使用此信息识别复苏活动。本文的主题是第一步，目标检测和跟踪基于卷积神经网络，然后进行后处理。结果：在20个视频的测试集上，活动期间物体检测的性能分别为96.97％（换气），100％（附着/移除心率传感器）和75％（吸气）。该系统还估计有71.16％的绩效的医疗保健提供者的数量。结论：提出的目标检测和跟踪系统在嘈杂的新生儿复苏视频中提供了有希望的结果。启示：这是对新生儿复苏事件进行全面分析的第一步，