A Unifying Method to Study Respiratory Sinus Arrhythmia Dynamics Implemented in a New Toolbox.
cycle-by-cycle
respiration
respiratory sinus arrhythmia
toolbox
Journal
eNeuro
ISSN: 2373-2822
Titre abrégé: eNeuro
Pays: United States
ID NLM: 101647362
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
09
06
2023
revised:
27
07
2023
accepted:
23
08
2023
medline:
30
10
2023
pubmed:
18
10
2023
entrez:
17
10
2023
Statut:
epublish
Résumé
Respiratory sinus arrhythmia (RSA), the natural variation in heart rate synchronized with respiration, has been extensively studied in emotional and cognitive contexts. Various time or frequency-based methods using the cardiac signal have been proposed to analyze RSA. In this study, we present a novel approach that combines respiratory phase and heart rate to enable a more detailed analysis of RSA and its dynamics throughout the respiratory cycle. To facilitate the application of this method, we have implemented it in an open-source Python toolbox called physio This toolbox includes essential functionalities for processing electrocardiogram (ECG) and respiratory signals, while also introducing this new approach for RSA analysis. Inspired by previous research conducted by our group, this method enables a cycle-by-cycle analysis of RSA providing the possibility to correlate any respiratory feature to any RSA feature. By employing this approach, we aim to gain a more accurate understanding of the neural mechanisms associated with RSA.
Identifiants
pubmed: 37848290
pii: ENEURO.0197-23.2023
doi: 10.1523/ENEURO.0197-23.2023
pmc: PMC10614108
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2023 Ghibaudo et al.
Déclaration de conflit d'intérêts
The authors declare no competing financial interests.
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