Object Detection during Newborn Resuscitation Activities

Oyvind Meinich-Bache, Kjersti Engan, Ivar Austvoll, Trygve Eftestol, Helge Myklebust, Ladislaus Blacy Yarrot, Hussein Kidanto, Hege Ersdal

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


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.

Original languageEnglish
Article number8744590
Pages (from-to)796-803
Number of pages8
JournalIEEE Journal of Biomedical and Health Informatics
Issue number3
Publication statusPublished - Mar 2020


  • Newborn resuscitation
  • automatic video analysis
  • convolutional neural networks
  • object detection


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