@misc{10481/93381,
year = {2024},
month = {2},
url = {https://hdl.handle.net/10481/93381},
abstract = {The incidence of premature births continues
to rise each year and premature babies require specialized
care in neonatal intensive care units (NICUs). The intermittent
monitoring of these babies, however, poses challenges
for clinicians in terms of visualizing and detecting meaningful
diagnostic trends. In order to address this issue, the
adoption of continuous, multi-parameter, electronic medical
record-keeping methods is promising in terms of leveraging
advanced analytics techniques and potentially improving
health outcomes. In this article, we present the
design and implementation of the Neonates Recording Platform
(NRP), a hardware-software tool to be deployed at the
bedside in a real NICU environment. The NRP enables data
from various sources to be collected, labelled, processed
and stored. We conducted tests involving the acquisition
of neonates’ physiological parameters, synchronized with
video recordings, in addition to real-time analysis of body
pose, with the capture of up to 33 reference points, and
audio files from both the infant and the environment. In
NRP, the collected data is organized hierarchically in a
portable format and is automatically cleaned and validated, thereby ensuring its usability for healthcare professionals
and data scientists. Additionally, NRP enables medical
staff to configure trials and add customized text or tagging
events. A significant contribution of the NRP platform is the
integration of a unique computer vision algorithm called
CardMed, which extracts physiological information (such
as heart rate, breath rate, and blood oxygenation) directly
from any monitoring device. The development of NRP involved
collaboration with medical staff and data scientists,
and evaluation took place at the NICU of the Puerta del Mar
University Hospital in Cádiz, Spain.},
publisher = {IEEE},
keywords = {Infants},
keywords = {Data collection system},
keywords = {Audio/video},
title = {NRP: A Multi-Source, Heterogeneous, Automatic Data Collection System for Infants in Neonatal Intensive Care Units},
doi = {10.1109/jbhi.2023.3306477},
author = {Pigueiras-del-Real, Janet and C. Gontard, Lionel and Benavente-Fernández, Isabel and Lubián-López, Simón P. and Gallero-Rebollo, Enrique and Ruiz-Zafra, Ángel},
}