• search hit 14 of 179
Back to Result List

Dynamical disentanglement in an analysis of oscillatory systems: an application to respiratory sinus arrhythmia

  • We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of theWe develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.show moreshow less

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details:Michael RosenblumORCiDGND, Martha Frühwirth, Maximilian MoserORCiD, Arkadij PikovskijORCiDGND
DOI:https://doi.org/10.1098/rsta.2019.0045
ISSN:1364-503X
ISSN:1471-2962
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/31656138
Title of parent work (English):Philosophical Transactions of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences
Publisher:Royal Society
Place of publishing:London
Publication type:Article
Language:English
Year of first publication:2019
Publication year:2019
Release date:2020/09/12
Tag:autonomic nervous system; phase dynamics; point process; vagal sympathetic activity
Volume:377
Issue:2160
Number of pages:14
Funding institution:the Marie Sklodowska-Curie GrantEuropean Union (EU) [642563]; Russian Science FoundationRussian Science Foundation (RSF) [17-12-01534]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
Peer review:Referiert
Publishing method:Open Access
Open Access / Bronze Open-Access
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.