Time-varying analysis methods and models for the respiratory and cardiac system coupling in graded exercise

The analysis of heart period series is a difficult task especially under graded exercise conditions. From all the information present in these series, we are the most interested in the coupling between respiratory and cardiac systems, known as respiratory sinus arrythmia. In this paper, we show that precise patterns concerning the respiratory frequency can be extracted from the heart period series. An evolutive model is introduced in order to achieve tracking of the main respiratory-related frequencies and their time-varying amplitudes. Since respiration acts to modulate the sinus rhythm, we relate the frequencies and amplitudes to this modulation by analyzing in detail its nonlinear transformation giving the heart period signal. This analysis is performed assuming stationary conditions but also in the realistic case where the mean heart period, the amplitude, and the frequency of the respiration are time-varying. Since this paper is devoted to the theoretical and complete presentation of the method used in a physiological study published elsewhere, the capabilities of our method will be illustrated in a realistic simulated case.

[1]  A. Nehorai,et al.  Adaptive power spectrum estimation algorithm for heart rate variability analysis , 1991, [1991] Proceedings Computers in Cardiology.

[2]  J. Taylor,et al.  Short‐term cardiovascular oscillations in man: measuring and modelling the physiologies , 2002, The Journal of physiology.

[3]  O Meste,et al.  Assessment of ventilatory thresholds during graded and maximal exercise test using time varying analysis of respiratory sinus arrhythmia , 2005, British Journal of Sports Medicine.

[4]  Peter Strobach.  The recursive companion matrix root tracker , 1997, IEEE Trans. Signal Process..

[5]  Arye Nehorai,et al.  Adaptive polynomial factorization by coefficient matching , 1991, IEEE Trans. Signal Process..

[6]  Henning Cammann,et al.  How to avoid misinterpretation of heart rate variability power spectra? , 2002, Comput. Methods Programs Biomed..

[7]  M. Malik.  Heart Rate Variability , 1996, Clinical cardiology.

[8]  Olivier Meste,et al.  Analysis of the respiratory and cardiac systems coupling in pyramidal exercise using a time-varying model , 2002, Computers in Cardiology.

[9]  P. Hunter,et al.  Stretch-induced changes in heart rate and rhythm: clinical observations, experiments and mathematical models. , 1999, Progress in biophysics and molecular biology.

[10]  Olivier Meste,et al.  Some considerations on the IPFM model for the heart rate variability analysis , 2003, Computers in Cardiology, 2003.

[11]  T E Brown,et al.  Contributions of tidal lung inflation to human R-R interval and arterial pressure fluctuations. , 1998, Journal of the autonomic nervous system.

[12]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[13]  Olivier Meste,et al.  Influences of breathing patterns on respiratory sinus arrhythmia in humans during exercise. , 2005, American journal of physiology. Heart and circulatory physiology.

[14]  Steven Kay,et al.  Modern Spectral Estimation: Theory and Application , 1988 .

[15]  Yves Grenier,et al.  Time-dependent ARMA modeling of nonstationary signals , 1983 .

[16]  Katrin Suder,et al.  One-dimensional, nonlinear determinism characterizes heart rate pattern during paced respiration. , 1998, American journal of physiology. Heart and circulatory physiology.

[17]  G. Baselli,et al.  Pole-tracking algorithms for the extraction of time-variant heart rate variability spectral parameters , 1995, IEEE Transactions on Biomedical Engineering.

[18]  K. Yana,et al.  A time domain approach for the fluctuation analysis of heart rate related to instantaneous lung volume , 1993, IEEE Transactions on Biomedical Engineering.

[19]  J A Dempsey,et al.  Respiratory sinus arrhythmia in humans: an obligatory role for vagal feedback from the lungs. , 1995, Journal of applied physiology.

[20]  Aneta Stefanovska,et al.  Nonlinear cardio-respiratory interactions revealed by time-phase bispectral analysis. , 2004, Physics in medicine and biology.

[21]  Marimuthu Palaniswami,et al.  Distortion properties of the interval spectrum of IPFM generated heartbeats for heart rate variability analysis , 2001, IEEE Transactions on Biomedical Engineering.

[22]  Pablo Laguna,et al.  Improved heart rate variability signal analysis from the beat occurrence times according to the IPFM model , 2000, IEEE Transactions on Biomedical Engineering.

[23]  A. Bezerianos,et al.  A modified Prony's method for tracking and monitoring the effects of autonomic nervous system blockade on heart rate variability , 1995, Computers in Cardiology 1995.

[24]  Solange Akselrod,et al.  Do the high-frequency indexes of HRV provide a faithful assessment of cardiac vagal tone? A critical theoretical evaluation , 2003, IEEE Transactions on Biomedical Engineering.