Estimation and power spectral analysis of heart instantaneous frequency (HIF) - a wavelet approach

Investigation of heart rate variability (HRV) has been the subject of considerable interest in the management of cardiac arrhythmia. Digital signal processing using instantaneous frequency and multiresolution analysis (Daubechies (db4) wavelet transforms) has been applied to estimate HRV without R point detection. The proposed method requires less memory for long term analysis as the ECG was measured with only 4 Hz sampling. Such a saving in memory makes it especially convenient to apply for long term analysis. The analysis of HRV using wavelet transforms was found to be very effective over conventional IIR filters. The sensitivity of the LF/HF ratio parameter increases with the Daubeches (db) based wavelet filter.

[1]  Allan Kardec Barros,et al.  Heart instantaneous frequency (HIF): an alternative approach to extract heart rate variability , 2001, IEEE Transactions on Biomedical Engineering.

[2]  Fusheng Yang,et al.  Modeling and decomposition of HRV signals with wavelet transforms , 1997, IEEE Engineering in Medicine and Biology Magazine.

[3]  Holger Adelmann Design of a PC-Based System for Time-Domain and Spectral Analysis of Heart Rate Variability, , 1999, Comput. Biomed. Res..

[4]  J. S. Sahambi,et al.  Using Wavelet Transforms for ECG Characterization , 1997 .

[5]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[6]  S. Cerutti,et al.  Time-variant power spectrum analysis for the detection of transient episodes in HRV signal , 1993, IEEE Transactions on Biomedical Engineering.

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

[8]  M. Merri,et al.  Sampling frequency of the electrocardiogram for spectral analysis of the heart rate variability , 1990 .

[9]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[10]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[11]  Lutz Trahms,et al.  Variability of the QRS signal in high-resolution electrocardiograms and magnetocardiograms , 2001, IEEE Transactions on Biomedical Engineering.

[12]  Randy K. Young Wavelet theory and its applications , 1993, The Kluwer international series in engineering and computer science.

[13]  S.N. Tandon,et al.  Using wavelet transforms for ECG characterization. An on-line digital signal processing system , 1997, IEEE Engineering in Medicine and Biology Magazine.

[14]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .