Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 56, Issue 7, Pages 1791-1802Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2009.2016349
Keywords
Adaptive filters; autoregressive (AR) processes; heart rate variability (HRV); point processes; respiratory sinus arrhythmia (RSA)
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Funding
- NCRR NIH HHS [RR-79] Funding Source: Medline
- NHLBI NIH HHS [R01-HL084502, R01 HL084502-03, R01 HL084502] Funding Source: Medline
- NIA NIH HHS [AG-9550] Funding Source: Medline
- NIDA NIH HHS [R01 DA015644, R01-DA015644] Funding Source: Medline
- NIGMS NIH HHS [GM-26691] Funding Source: Medline
- NIH HHS [DP1 OD003646, DP1 OD003646-03, DP1-OD003646] Funding Source: Medline
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Tracking the autonomic control and respiratory sinus arrhythmia (RSA) from electrocardiogram and respiratory measurements is an important problem in cardiovascular control. We propose a point process adaptive filter algorithm based on an inverse Gaussian model to track heart beat intervals that incorporates respiratory measurements as a covariate and provides an analytic form for computing a dynamic estimate of RSA gain. We use Kolmogorov-Smirnov tests and autocorrelation function analyses to assess model goodness-of-fit. We illustrate the properties of the new dynamic estimate of RSA in the analysis of simulated heart beat data and actual heart beat data recorded from subjects in a four-state postural study of heart beat dynamics: control, sympathetic blockade, parasympathetic blockade, and combined sympathetic and parasympathetic blockade. In addition to giving an accurate description of the heart beat data, our adaptive filter algorithm confirms established findings pointing at a vagally mediated RSA and provides a new dynamic RSA estimate that can be used to track cardiovascular control between and within a broad range of postural, pharmacological, and age conditions. Our paradigm suggests a possible framework for designing a device for ambulatory monitoring and assessment of autonomic control in both laboratory research and clinical practice.
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