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Related Experiment Video

Updated: Dec 26, 2025

Multi-system Monitoring for Identification of Seizures, Arrhythmias and Apnea in Conscious Restrained Rabbits
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Activity Recognition From Newborn Resuscitation Videos.

Oyvind Meinich-Bache, Simon Lennart Austnes, Kjersti Engan

    IEEE Journal of Biomedical and Health Informatics
    |March 10, 2020
    PubMed
    Summary

    A deep learning system, ORAA-net, analyzes low-quality videos to recognize newborn resuscitation activities. This technology can help improve survival rates and optimize treatment guidelines for birth asphyxia.

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    Area of Science:

    • Medical technology
    • Artificial intelligence in healthcare
    • Neonatal care

    Background:

    • Birth asphyxia is a major cause of neonatal mortality globally.
    • Effective newborn resuscitation requires immediate and high-quality interventions.
    • Analyzing resuscitation effectiveness is crucial for improving outcomes.

    Purpose of the Study:

    • To develop an automated system for recognizing activities during newborn resuscitation from low-quality videos.
    • To generate timelines of key resuscitation events like ventilation, stimulation, and suction.
    • To analyze the impact of resuscitation activities on newborn outcomes.

    Main Methods:

    • A two-step deep neural network system, ORAA-net, was proposed.
    • Step 1: Object detection and tracking using Convolutional Neural Networks (CNN).
    • Step 2: Activity recognition using 3D CNNs on detected regions.

    Main Results:

    • ORAA-net achieved high accuracy in recognizing activities: 77.67% precision, 77.64% recall, and 92.40% accuracy.
    • The system also estimated the number of healthcare providers with 68.32% accuracy.
    • The model demonstrated effectiveness in noisy, low-quality video data.

    Conclusions:

    • The ORAA-net system is a viable tool for object detection and activity recognition in challenging newborn resuscitation videos.
    • Automated analysis of resuscitation videos can support quality improvement initiatives.
    • Further analysis can optimize treatment guidelines and training for better newborn survival.