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Arfima-Garch Modeling of Hrv: Clinical Application in Acute Brain Injury

Preprint

<p>Chapter in Book: Complexity and Nonlinearity in Cardiovascular Signals, ( Eds Riccardo\&nbsp;Barbieri, Enzo Pasquale\&nbsp;Scilingo, Gaetano\&nbsp;Valenza), Springer International Publishing AG 2017</p> <p>https://link.springer.com/book/10.1007/978-3-319-58709-7 , https://doi.org/10.1007/978-3-319-58709-7</p> <p>Chapter Abstract: In the last decade, several HRV based novel methodologies for describing and assessing heart rate dynamics have been proposed in the literature with the aim of risk assessment. Such methodologies attempt to describe the non-linear and complex characteristics of HRV, and hereby the focus is in two of these characteristics, namely long memory and heteroscedasticity with variance clustering. The ARFIMA-GARCH modeling considered here allows the quantification of long range correlations and time-varying volatility. ARFIMA-GARCH HRV analysis is integrated with multimodal brain monitoring in several acute cerebral phenomena such as intracranial hypertension, decompressive craniectomy and brain death. The results indicate that ARFIMA-GARCH modeling appears to reflect changes in Heart Rate Variability (HRV) dynamics related both with the Acute Brain Injury (ABI) and the medical treatments effects.</p>

Rute Almeida

C Dias

ME Silva

Publication

Year of publication: 2017

Pages: 451-468

Date published: 08/2017

Identifiers

ISBN: 978-3-319-58709-7

Alternative Titles

Preprint

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