Evidence map›Paper›PMID 37848290›Full record

ArticleeNeuro2023

A Unifying Method to Study Respiratory Sinus Arrhythmia Dynamics Implemented in a New Toolbox.

Valentin Ghibaudo, Jules Granget, Matthias Dereli, Nathalie Buonviso, Samuel Garcia

Abstract read
In one paragraph

Article in eNeuro, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Valentin GhibaudoCentre de Recherche en Neuroscience de Lyon, Lyon, 69500, France valentin.ghibaudo@inserm.fr.ORCID 0009-0008-3152-476X
Jules GrangetCentre de Recherche en Neuroscience de Lyon, Lyon, 69500, France.
Matthias DereliCentre de Recherche en Neuroscience de Lyon, Lyon, 69500, France.
Nathalie BuonvisoCentre de Recherche en Neuroscience de Lyon, Lyon, 69500, France.ORCID 0000-0002-0018-1695
Samuel GarciaCentre de Recherche en Neuroscience de Lyon, Lyon, 69500, France.ORCID 0000-0001-6389-9779

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Respiratory Sinus ArrhythmiaArrhythmia, SinusElectrocardiographyHeartHeart RateHumansRespirationcycle-by-cyclerespirationrespiratory sinus arrhythmiatoolbox

Identifiers

PMID37848290
PMCPMC10614108

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.