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NewbornTime – Improved newborn care based on video and artificial intelligence

The NewbornTime project is about improved newborn care by using artificial intelligence (AI) for activity and event recognition in video from the time during and after birth.

Publisert: Endret:
Facts
Funding

The project is funded by NRC (project no. 320968, IKTPLUSS Collaborative and Knowledge-building Project), Fondation Idella and Helse Vest.

Partners

University of Stavanger (lead), Stavanger University Hospital (SUS), Laerdal Medical and bitYoga.

2 million – the number of newborn babies who could be saved each year if we end preventable newborn mortality.

SavetheChildren.org

Deprivation of oxygen to an infant during and after birth might lead to birth asphyxia, one of the leading causes of newborn deaths, cerebral palsy and other long-term damage. According to guidelines, a newborn in need of help to start breathing should be resuscitated immediately after birth. Resuscitation activities include stimulating, clearing airways, and perform bag-mask-ventilation. In Norway, approximately 10% of term infants need stimulation and around 3% need bag-mask ventilation.

NewbornTime will produce a timeline describing events and activities performed on a newborn. Accurate time of birth will be detected using AI models from thermal videos collected in the delivery room. Activity recognition will be performed using AI in the form of deep convolutional neural networks (CNN) on thermal and RGB video from the resuscitation. The system will be designed to recognize multiple time-overlapping activities. Care will be given to make the AI models robust, reliable, general, and adaptive to be able to use it at different hospitals and settings. The timelines will be used to evaluate compliance to guidelines and identify successful resuscitation activity patterns. It can further be useful in a de-briefing and quality improvement tool.

The project is a collaboration between University of Stavanger (UiS), Stavanger University Hospital (SUS), Laerdal Medical and BitYoga. UiS, SUS and Laerdal has long experience in collaborative research on newborn care. They have documented promising results on detecting activities using resuscitation videos from a hospital in Tanzania. In NewbornTime the data collection will be performed at SUS. BitYoga and Laerdal will ensure smart GDPR compliant data-contracts and data-platforms. UiS will develop site-adaptive AI methods for activity recognition in video.

Information page for participants: In English and in Norwegian.

Workshop on newborn resuscitation

University of Stavanger and Stavanger university hospital will hold a workshop Friday December 3rd.

Bilde av Stavanger Universitetssjukehus (SUS)

Date: 03 December 2021

Location:  University of Stavanger, Kjølv Egelands building (KE) Room E-102

The workshop is open to the public, anyone can come to the general program from 10:00-11:50 and 12:30-13:40, no registration necessary. It is also possible to follow the workshop remotely by joining the zoom link:

https://stavanger.zoom.us/j/61488421368?pwd=c1daQ25qWWRJZk9Kcm1MNUlwRmc1Zz09

Meeting ID: 614 8842 1368 , password: 400656

Program

10:00-10:05 Welcome

10:05-10:35 Hege Ersdal (SUS): Updated newborn resuscitation guidelines and Safer Births studies

10:35-10:50 Jørgen Linde (SUS): Research project in Tanzania – transfer value to newborn resuscitation in Norway

10:50-11:05 Discussion and small break

11:05-11:20 Siren Rettedal (SUS): Safer Births SUS – which knowledge gaps are we addressing and results so far

11:20-11:40 Joanna Haynes (SUS): Newborn simulation research at SUS – what did we learn from the studies?

11:40-11:50 Open discussion

11:50-12:30 Lunch (only for partners and presenters)

12:30-12:45 Kjersti Engan (UiS): NewbornTime – short about project and status

12:45-13:00 Chunming Rong (BitYoga): Digital consent solution and data security

13:00-13:15 Sara Brunner (Laerdal Med.): Semi-automatic data collection: how it all works

13:15-13:30 Helge Myklebust (Laerdal Med.): Experience gained using objective data from resuscitations

13:30-13:40 Siren Rettedal (SUS): Subproject funded: “NewbornTime Debrief and Simulation – Making Every Resuscitation a Learning Event”

13:40-14:10 Partners only (closed meeting); Planning ahead for NewbornTime: publications, abstracts, data collection etc.

14:10-15:00 Partners only (closed meeting); Open discussion

NewbornTime in the news

We will push the research front in robust and adaptive Artificial Intelligence (AI) for activity recognition from video and thermal video analysis. We will develop automated systems useful for research, debriefing and feedback on newborn care around time of birth. NewbornTime means AI for safer births.

University of Stavanger

NewbornTime is making every resuscitation a learning event. We want to build a culture for continuous data-driven quality improvement.

Stavanger University Hospital

This project will develop important, new technology to automate consent and data analysis. It will reduce the workload in the hospital and the new data will guide quality improvement. To make births safer.

Laerdal Medical

BitYoga develops a Consent Management Platform for NewbornTime based on blockchain technology, reliable communication protocol and encryption, protecting user data in an absolutely secure manner.

BitYoga

Key personnel, University of Stavanger

Professor
51832008
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Førsteamanuensis II
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Stipendiat
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Professor
51832035
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Postdoktor
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science

Stavanger University Hospital (SUS)

Siren Rettedal
MD PhD
Stavanger University Hospital (SUS)
Hanne Pike
Stavanger University Hospital (SUS)
Hege Langli Ersdal
MD, PhD
Stavanger University Hospital (SUS)
Joanna Claire Haynes
MD, PhD student
Stavanger University Hospital (SUS)
Amalie Kibsgaard-Petersen
MD
Stavanger University Hospital (SUS)
Peder Aleksander Bjorland
MD
Stavanger University Hospital (SUS)

Laerdal Medical

Helge Myklebust
Head of strategic research, Laerdal Medical
Researcher
Laerdal Medical AS
Førsteamanuensis II
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Software developer
Laerdal Medical AS
Software developer
Laerdal Medical AS

BitYoga

Long Cui
BitYoga
Professor
51832013
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Seniorrådgiver
51832182
Faculty of Science and Technology

Faculty Administration TN

Kontor for forskningsadministrative tjenester

Partners