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Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals
In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772900/ https://www.ncbi.nlm.nih.gov/pubmed/35049717 http://dx.doi.org/10.3390/bioengineering9010008 |
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author | Ponsiglione, Alfonso Maria Amato, Francesco Romano, Maria |
author_facet | Ponsiglione, Alfonso Maria Amato, Francesco Romano, Maria |
author_sort | Ponsiglione, Alfonso Maria |
collection | PubMed |
description | In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), there are still shadows hindering a comprehensive understanding of how linear and nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose a straightforward processing and modeling route for a deeper understanding of the relationships between the characteristics of the FHR signal. A multiparametric modeling and investigation of the factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural networks. The obtained results show that linear features are more influential compared to nonlinear ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable and reliable information to clinicians and researchers. |
format | Online Article Text |
id | pubmed-8772900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87729002022-01-21 Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals Ponsiglione, Alfonso Maria Amato, Francesco Romano, Maria Bioengineering (Basel) Article In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), there are still shadows hindering a comprehensive understanding of how linear and nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose a straightforward processing and modeling route for a deeper understanding of the relationships between the characteristics of the FHR signal. A multiparametric modeling and investigation of the factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural networks. The obtained results show that linear features are more influential compared to nonlinear ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable and reliable information to clinicians and researchers. MDPI 2021-12-28 /pmc/articles/PMC8772900/ /pubmed/35049717 http://dx.doi.org/10.3390/bioengineering9010008 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ponsiglione, Alfonso Maria Amato, Francesco Romano, Maria Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals |
title | Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals |
title_full | Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals |
title_fullStr | Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals |
title_full_unstemmed | Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals |
title_short | Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals |
title_sort | multiparametric investigation of dynamics in fetal heart rate signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772900/ https://www.ncbi.nlm.nih.gov/pubmed/35049717 http://dx.doi.org/10.3390/bioengineering9010008 |
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