Abstract
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 is 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, like 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
Abstract (translated)
出生窒息是低资源国家中新生儿死亡的主要原因。国际指南提供了治疗建议,但不同的治疗方法的重要性和效果并未得到充分探讨。在坦桑尼亚的新生儿复苏期间,可用数据收集来分析复苏活动和新生儿的反应。分析的一个重要步骤是创建活动时间线图,其中包括呼吸、吸氧、刺激等活动。方法:可用的视频录制质量较差,存在大量差异。我们提出了一种两步过程,以检测可能同时发生的活动。第一步是检测和跟踪相关物体,如塑料袋口罩复苏器、心率传感器等。第二步是使用这些信息识别复苏活动。本文的主题是第一步,对象检测和跟踪基于卷积神经网络,然后进行 post 处理。结果:在活动中的对象检测性能在 96.97 %(呼吸)、100 %(插入/移除心率传感器)和 75 %(吸氧)的情况下表现良好。系统还估计了有 71.16 % 表现良好的医疗专业人员数量。结论:提出的对象检测和跟踪系统在噪音突出的新生儿复苏视频中表现出良好的结果。意义:这是深入分析新生儿复苏事件的第一步,这可能提供有关不同新生儿复苏活动重要性和效果的重要见解。
URL
https://arxiv.org/abs/2303.07790
