A Method for the Analysis of Respiratory Sinus Arrhythmia Using Continuous Wavelet Transforms

A continuous wavelet transform-based method is presented to study the nonstationary strength and phase delay of the respiratory sinus arrhythmia (RSA). The RSA is the cyclic variation of instantaneous heart rate at the breathing frequency. In studies of cardio-respiratory interaction during sleep, paced breathing or postural changes, low respiratory frequencies, and fast changes can occur. Comparison on synthetic data presented here shows that the proposed method outperforms traditional short-time Fourier-transform analysis in these conditions. On the one hand, wavelet analysis presents a sufficient frequency-resolution to handle low respiratory frequencies, for which time frames should be long in Fourier-based analysis. On the other hand, it is able to track fast variations of the signals in both amplitude and phase for which time frames should be short in Fourier-based analysis.

[1]  Pierre-François Migeotte,et al.  A Novel Algorithm for the Heart Rate Variability Analysis of Short-Term Recordings: Polar Representation of Respiratory Sinus Arrhythmia , 1999, Comput. Biomed. Res..

[2]  Hsiao-Lung Chan,et al.  Time-Frequency Analysis of Heart Rate Variability During Transient Segments , 2001, Annals of Biomedical Engineering.

[3]  Luca T. Mainardi,et al.  Advanced spectral methods for detecting dynamic behaviour , 2001, Autonomic Neuroscience.

[4]  D L Eckberg,et al.  Human responses to upright tilt: a window on central autonomic integration , 1999, The Journal of physiology.

[5]  Keith R. Godfrey,et al.  Comparison of methods for harmonic wavelet analysis of heart rate variability , 1998 .

[6]  M. Piepoli,et al.  Origin of respiratory sinus arrhythmia in conscious humans. An important role for arterial carotid baroreceptors. , 1997, Circulation.

[7]  Alain Muzet,et al.  Sleep Processes Exert a Predominant Influence on the 24-h Profile of Heart Rate Variability , 2002, Journal of biological rhythms.

[8]  R. Cohen,et al.  Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. , 1981, Science.

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

[10]  J. Saul,et al.  Transfer function analysis of the circulation: unique insights into cardiovascular regulation. , 1991, The American journal of physiology.

[11]  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.

[12]  J. Kingsbury.  The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance , 2004 .

[13]  S. Akselrod,et al.  Selective discrete Fourier transform algorithm for time-frequency analysis: method and application on simulated and cardiovascular signals , 1996, IEEE Transactions on Biomedical Engineering.

[14]  J B West,et al.  Microgravity reduces sleep-disordered breathing in humans. , 2001, American journal of respiratory and critical care medicine.

[15]  Paul S. Addison,et al.  The Illustrated Wavelet Transform Handbook , 2002 .

[16]  V Pichot,et al.  Wavelet transform to quantify heart rate variability and to assess its instantaneous changes. , 1999, Journal of applied physiology.