BaroWavelet: An R-based tool for dynamic baroreflex evaluation through wavelet analysis techniques.

Baroreflex Baroreflex dysfunction Baroreflex sensitivity Blood pressure control Dysautonomia R programming language Wavelet analysis

Journal

Computer methods and programs in biomedicine
ISSN: 1872-7565
Titre abrégé: Comput Methods Programs Biomed
Pays: Ireland
ID NLM: 8506513

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 11 05 2023
revised: 28 07 2023
accepted: 07 08 2023
medline: 14 11 2023
pubmed: 10 9 2023
entrez: 9 9 2023
Statut: ppublish

Résumé

Baroreflex sensitivity constitutes an indicator of the function of the baroreceptor control mechanism of blood pressure levels. It can be computed after estimating heart rate and blood pressure variability. We propose a novel tool for the evaluation of baroreflex sensitivity using wavelet analysis methods. This tool, known as BaroWavelet, incorporates an algorithm proposal based on the analysis methodology of the RHRV software package, as well as other conventional techniques. Our objectives are to develop and evaluate the tool, by testing its ability to detect changes in baroreflex sensitivity in humans. The code for this tool was designed in the R programming environment and was organized into two analysis routines and a graphical interface. Simulated recordings of blood pressure and inter-beat intervals were employed for an initial evaluation of the tool in a controlled environment. Finally, similar recordings obtained during supine and orthostatic postural evaluations, from patients that belonged to the open-access EUROBAVAR data set, were analyzed. BaroWavelet identified the scripted changes of the baroreflex sensitivity in the simulated data. The algorithm proposal was also able to better retain additional information regarding the dynamics of the baroreflex. In the EUROBAVAR subjects, baroreflex sensitivity components were significantly smaller during orthostatism when compared with the supine position. BaroWavelet managed to characterize baroreflex dynamics from the recordings, which were consistent with the findings reported in the literature. This demonstrates its effectiveness to perform these analyses. We suggest that this tool may be of use in research and for the evaluation of baroreflex sensitivity with clinical and therapeutic purposes. The new tool is available at the official GitHub repository of the Autonomic Nervous System Unit of the University of Málaga (https://github.com/CIMES-USNA-UMA/BaroWavelet).

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Baroreflex sensitivity constitutes an indicator of the function of the baroreceptor control mechanism of blood pressure levels. It can be computed after estimating heart rate and blood pressure variability. We propose a novel tool for the evaluation of baroreflex sensitivity using wavelet analysis methods. This tool, known as BaroWavelet, incorporates an algorithm proposal based on the analysis methodology of the RHRV software package, as well as other conventional techniques. Our objectives are to develop and evaluate the tool, by testing its ability to detect changes in baroreflex sensitivity in humans.
METHODS METHODS
The code for this tool was designed in the R programming environment and was organized into two analysis routines and a graphical interface. Simulated recordings of blood pressure and inter-beat intervals were employed for an initial evaluation of the tool in a controlled environment. Finally, similar recordings obtained during supine and orthostatic postural evaluations, from patients that belonged to the open-access EUROBAVAR data set, were analyzed.
RESULTS RESULTS
BaroWavelet identified the scripted changes of the baroreflex sensitivity in the simulated data. The algorithm proposal was also able to better retain additional information regarding the dynamics of the baroreflex. In the EUROBAVAR subjects, baroreflex sensitivity components were significantly smaller during orthostatism when compared with the supine position.
CONCLUSIONS CONCLUSIONS
BaroWavelet managed to characterize baroreflex dynamics from the recordings, which were consistent with the findings reported in the literature. This demonstrates its effectiveness to perform these analyses. We suggest that this tool may be of use in research and for the evaluation of baroreflex sensitivity with clinical and therapeutic purposes. The new tool is available at the official GitHub repository of the Autonomic Nervous System Unit of the University of Málaga (https://github.com/CIMES-USNA-UMA/BaroWavelet).

Identifiants

pubmed: 37688995
pii: S0169-2607(23)00424-8
doi: 10.1016/j.cmpb.2023.107758
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

107758

Informations de copyright

Copyright © 2023. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

A Chao-Ecija (A)

Autonomic Nervous System Unit, CIMES, School of Medicine, University of Málaga, Spain.

M S Dawid-Milner (MS)

Autonomic Nervous System Unit, CIMES, School of Medicine, University of Málaga, Spain; Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain. Electronic address: msdawid@uma.es.

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Classifications MeSH