The newborn delivery room of tomorrow: emerging and future technologies

Abstract

Advances in neonatal care have resulted in improved outcomes for high-risk newborns with technologies playing a significant part although many were developed for the neonatal intensive care unit. The care provided in the delivery room (DR) during the first few minutes of life can impact short- and long-term neonatal outcomes. Increasingly, technologies have a critical role to play in the DR particularly with monitoring and information provision. However, the DR is a unique environment and has major challenges around the period of foetal to neonatal transition that need to be overcome when developing new technologies. This review focuses on current DR technologies as well as those just emerging and further over the horizon. We identify what key opinion leaders in DR care think of current technologies, what the important DR measures are to them, and which technologies might be useful in the future. We link these with key technologies including respiratory function monitors, electoral impedance tomography, videolaryngoscopy, augmented reality, video recording, eye tracking, artificial intelligence, and contactless monitoring. Encouraging funders and industry to address the unique technological challenges of newborn care in the DR will allow the continued improvement of outcomes of high-risk infants from the moment of birth. IMPACT: Technological advances for newborn delivery room care require consideration of the unique environment, the variable patient characteristics, and disease states, as well as human factor challenges. Neonatology as a speciality has embraced technology, allowing its rapid progression and improved outcomes for infants, although innovation in the delivery room often lags behind that in the intensive care unit. Investing in new and emerging technologies can support healthcare providers when optimising care and could improve training, safety, and neonatal outcomes.

Fig. 1. Survey respondents’ (n = 60) ranking of the importance of key monitoring measures within the delivery room.

SpO₂ oxygen saturations, CO₂ carbon dioxide, O₂ cerebral oxygenation.

Fig. 2. Example heat map after analysis of providers’ gaze behaviour in a simulated resuscitation scenario.

Visual attention patterns can be analysed allowing different or new technologies to be evaluated.

Fig. 3. Process of training a computer system to recognise resuscitation actions using computer vision and artificial intelligence (AI).

(1) Image training data set manually labelled, categorising actions for the algorithm. (2) New data set (video) is inputted into the AI algorithm for analysis. (3) The algorithm pixelates items to label and track them. (4) Output allows quantification of important actions, their timing, duration, and frequency. Running in real time has the potential to support stabilisation/resuscitation algorithms to avoid deviations or errors especially in settings lacking experienced support.

Fig. 4. Survey ranking by respondents (n = 60) for new technology priorities within the delivery room of the future.

AI artificial intelligence, NIRS near infrared spectroscopy.