Patricio Fuentealba, Alfredo Illanes, Frank Ortmeier: Foetal heart rate signal spectral analysis by using time-varying autoregressive modelling. In: Current Directions in Biomedical Engineering, 4 (1), S. 579–582, 2018.

Abstract

During labour, foetal monitoring enables clinicians to prevent potential adverse outcomes, whose surveillance procedure is commonly based on analysis of cardiotocographic (CTG) signals. Unfortunately, this procedure is difficult because it involves human interpretation of highly complex signals. In order to improve the CTG assessment, different approaches based on signal processing techniques have been proposed. However, most of them do not consider the progression of the foetal response over time. In this work, we propose to study such progression along the foetal heart rate (FHR) signal by using spectral analysis based on time-varying autoregressive modelling. The main idea is to investigate if a particular FHR signal episode in the time-domain reflects dynamical changes in the frequency-domain that can help to assess the foetal condition. Results show that each FHR deceleration leaves a particular time-varying frequency signature described by the spectral energy components which could help to distinguish between a normal and a pathological foetus.

BibTeX (Download)

@article{fuentealba2018foetal,
title = {Foetal heart rate signal spectral analysis by using time-varying autoregressive modelling},
author = {Patricio Fuentealba and Alfredo Illanes and Frank Ortmeier},
url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2019/11/fuentealba2018foetal.pdf},
doi = {10.1515/cdbme-2018-0139},
year  = {2018},
date = {2018-09-22},
journal = {Current Directions in Biomedical Engineering},
volume = {4},
number = {1},
pages = {579--582},
publisher = {De Gruyter},
abstract = {During labour, foetal monitoring enables clinicians to prevent potential adverse outcomes, whose surveillance procedure is commonly based on analysis of cardiotocographic (CTG) signals. Unfortunately, this procedure is difficult because it involves human interpretation of highly complex signals. In order to improve the CTG assessment, different approaches based on signal processing techniques have been proposed. However, most of them do not consider the progression of the foetal response over time. In this work, we propose to study such progression along the foetal heart rate (FHR) signal by using spectral analysis based on time-varying autoregressive modelling. The main idea is to investigate if a particular FHR signal episode in the time-domain reflects dynamical changes in the frequency-domain that can help to assess the foetal condition. Results show that each FHR deceleration leaves a particular time-varying frequency signature described by the spectral energy components which could help to distinguish between a normal and a pathological foetus.},
keywords = {Autoregressive model, cardiotocograph, Fetal monitoring, FHR, Time-varying spectral analysis},
pubstate = {published},
tppubtype = {article}
}