Predicting Respiratory Depression in Neonates using Intra-arterial Pressure Measurements

Aleksandar Jeremic, Dejan Nikolic

2019

Abstract

Respiratory problems are one of the most common reasons for neonatal intensive care unit (NICU) admission of newborns. It has been estimated that as much as 29% of late preterm infants develop high respiratory morbidity. To this purpose invasive ventilation is often necessary for their treatment in NICU. These patients usually have underdeveloped respiratory system with deficiencies such as small airway caliber, few collateral airways, compliant chest wall, poor airway stability, and low functional residual capacity. Consequently ventilation control has been subject of considerable research interest. In this paper we propose an algorithm for detection of respiratory depression by predicting the onset of pO2 depressions using intra-arterial pressure measurements and second order statistical properties of these signals. We calculate the average covariance matrix of intra-arterial pressure measurements in the absence of respiratory depression. We then use this matrix as a reference measure and monitor the changes in the actual covariance matrix measurements. We predict the onset of respiratory depression once the distance is larger than empirically determined threshold. We demonstrate the applicability of our results using a real data set.

Paper Citation

in Harvard Style

Jeremic A. and Nikolic D. (2019). Predicting Respiratory Depression in Neonates using Intra-arterial Pressure Measurements. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 4: BIOSIGNALS; ISBN 978-989-758-353-7, SciTePress, pages 237-240. DOI: 10.5220/0007576802370240

in Bibtex Style

@conference{biosignals19,
author={Aleksandar Jeremic and Dejan Nikolic},
title={Predicting Respiratory Depression in Neonates using Intra-arterial Pressure Measurements},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 4: BIOSIGNALS},
year={2019},
pages={237-240},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007576802370240},
isbn={978-989-758-353-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 4: BIOSIGNALS
TI - Predicting Respiratory Depression in Neonates using Intra-arterial Pressure Measurements
SN - 978-989-758-353-7
AU - Jeremic A.
AU - Nikolic D.
PY - 2019
SP - 237
EP - 240
DO - 10.5220/0007576802370240
PB - SciTePress