A Unified Point Process Probabilistic Framework to Assess Heartbeat Dynamics and Autonomic Cardiovascular Control

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A Unified Point Process Probabilistic Framework to Assess Heartbeat Dynamics and Autonomic Cardiovascular Control

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dc.contributor.author Chen, Zhe
dc.contributor.author Purdon, Patrick Lee
dc.contributor.author Brown, Emery Neal
dc.contributor.author Barbieri, Riccardo
dc.date.accessioned 2012-08-03T18:26:24Z
dc.date.issued 2012
dc.identifier.citation Chen, Zhe, Patrick L. Purdon, Emery N. Brown, and Riccardo Barbieri. 2012. A unified point process probabilistic framework to assess heartbeat dynamics and autonomic cardiovascular control. Frontiers in Physiology 3: 4. en_US
dc.identifier.issn 1664-042X en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:9366538
dc.description.abstract In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model’s statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (baroreflex) sensitivity (BRS), are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second-order non-linearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of non-linearity. We here present a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, non-invasive assessment in clinical practice. We also discuss the limitations and other alternative modeling strategies of our point process approach. en_US
dc.language.iso en_US en_US
dc.publisher Frontiers Research Foundation en_US
dc.relation.isversionof doi:10.3389/fphys.2012.00004 en_US
dc.relation.hasversion http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269663/pdf/ en_US
dash.license LAA
dc.subject autonomic cardiovascular control en_US
dc.subject heart rate variability en_US
dc.subject baroreflex sensitivity en_US
dc.subject respiratory sinus arrhythmia en_US
dc.subject point process en_US
dc.subject Wiener-Volterra expansion en_US
dc.subject general anesthesia en_US
dc.title A Unified Point Process Probabilistic Framework to Assess Heartbeat Dynamics and Autonomic Cardiovascular Control en_US
dc.type Journal Article en_US
dc.description.version Version of Record en_US
dc.relation.journal Frontiers in Physiology en_US
dash.depositing.author Purdon, Patrick Lee
dc.date.available 2012-08-03T18:26:24Z

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