AI-Based Thermal Video Analysis in Privacy-Preserving Healthcare: A Case Study on Detecting Time of Birth
Journal:
arXiv
Published Date:
Feb 5, 2025
Abstract
Approximately 10% of newborns need some assistance to start breathing and 5\%
proper ventilation. It is crucial that interventions are initiated as soon as
possible after birth. Accurate documentation of Time of Birth (ToB) is thereby
essential for documenting and improving newborn resuscitation performance.
However, current clinical practices rely on manual recording of ToB, typically
with minute precision. In this study, we present an AI-driven, video-based
system for automated ToB detection using thermal imaging, designed to preserve
the privacy of healthcare providers and mothers by avoiding the use of
identifiable visual data. Our approach achieves 91.4% precision and 97.4%
recall in detecting ToB within thermal video clips during performance
evaluation. Additionally, our system successfully identifies ToB in 96% of test
cases with an absolute median deviation of 1 second compared to manual
annotations. This method offers a reliable solution for improving ToB
documentation and enhancing newborn resuscitation outcomes.
