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Spectral Analysis of Heart Rate Variability Signals using Stockwell-Transform

Ram Sevak

Abstract


This paper introduces the use of Stockwell transform (ST) for spectral analysis of heart rate variability (HRV) signals in time-frequency domain. The ST is depicted numerically and compared with well-liked method of wavelet transform known as continuous Morlet wavelet transform (CMWT). The results of this study show that the normalized mean power and total normalized power in VLF (0.004–0.04 Hz), LF (0.04–0.15 Hz) and HF (0.15–0.4 Hz) were improved compared to CMWT for statistical significance value of p=0.00016 and P<0.00001. For this analysis, electrocardiogram (ECG) was recorded in fifteen normal subjects (mean age approximate 28, range 23–34 years and mean height approximate 162 cm) in supine position for twenty minutes.

Keywords: Stockwell transform, scalogram, normalized mean power, ectopic beat, trend

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References


Akselrod S, Gordon D, Ubel FA, et al. Power Spectrum Analysis of Heart Rate Fluctuation: A Quantitative Probe of Beat-to-Beat Cardiovascular Control. J Sci. 1981; 213: 220–2p.

Fallen E.L., Kamath M.V., Ghista D.N. Power Spectrum of Heart Rate Variability: A Non-Invasive Test of Integrated Neurocardiac Function. Clin Invest Med. 1988; 11: 331–40p.

Pomeranz B, Macaulay RJ, Caudill MA, et al. Assessment of Autonomic Function in Humans by Heart Rate Spectral Analysis. Am J Physiol. 1985; 248: 151–3p.

Stein PK, Rich MW, Rottman JN, et al. Stability of Index of Heart Rate Variability in Patients with Congestive Heart Failure. A Heart J. 1995; 129: 975–81p.

Burger AJ, Charlamb M, Weinrauch LA, et al. Short and Long-Term Reproducibility of Heart Rate Variability in Patients with Long Standing Type I Diabetes Mellitus. Am J Cardiol. 1997; 80: 1198–1202p.

Nolan J., Flapan A.D., Goodfield N.E., et al. Measurement of Parasympathetic Activity from 24-Hour Ambulatory Electro-cardiograms and its Reproducibility and Sensitivity in Normal Subjects, Patients with Symptomatic Myocardial Ischemia, and Patients with Diabetes Mellitus. Am J Cardiol. 1996; 77: 154–8p.

Ewing D.J., Neilson J.M., Shapiro C.M., et al. Twenty Four Hour Heart Rate Variability: Effects of Posture, Sleep, and Time of Day in Healthy Controls and Comparison with Bedside Tests of Autonomic Function in Diabetic Patients. Br Heart J. 1991; 65: 239–44p.

Malpas S.C., Maling T.J. Heart-Rate Variability and Cardiac Autonomic Function in Diabetes. J Diabetes. 1990; 39: 1177–81p.

Konrady A.O., Rudomanov O.G., Yacovleva O.I., et al. Power Spectral Components of Heart Rate Variability in Different Types of Cardiac Remodeling in Hypertensive Patients. Med Sci Moni. 2001; 7: 58–63p.

Stein P.K., Kleiger R.E. Insights from the Study of Heart Rate Variability. Annu Rev Med. 1999; 50: 249–61p.

Scalvini S., Volterrani M., Zanelli E., et al. Is Heart Rate Variability a Reliable Method to Assess Autonomic Modulation in Left Ventricular Dysfunction and Heart Failure? Assessment of Autonomic Modulation with Heart Rate Variability. Int J Cardiol. 1998; 67: 9–17p.

Bigger T., Fleiss J.L., Steinman R.C., et al. RR Variability in Healthy, Middle-Aged Persons Compared with Patients with Chronic Coronary Heart Disease or Recent Acute Myocardial Infarction. Circulation. 1995; 91: 1936–43p.

Weber F., Schneider H., Von Arnim T., et al. Heart Rate Variability and Ischemia in Patients with Coronary Heart Disease and Stable Angina Pectoris; Influence of Drug Therapy and Prognostic Value. TIBBS Investigators Group. Total Ischemic Burden Bisoprolol Study. Eur Heart J. 1999; 20: 38–50p.

Van Boven A.J., Jukema J.W., Haaksma J., et al. Depressed Heart Rate Variability is Associated with Events in Patients with Stable Coronary Artery Disease and Preserved Left Ventricular Function. Am Heart J. 1998; 135: 571–6p.

Nolan J., Batin P.D., Andrews R., et al. Prospective Study of Heart Rate Variability and Mortality in Chronic Heart Failure: Results of the United Kingdom Heart Failure Evaluation and Assessment of Risk Trial (UK-Heart). J Circulation. 1998; 98: 1510–16p.

Dantas E.M., Lima Sant M. Spectral Analysis of Heart Rate Variability with the Autoregressive Method: What Model Order to Choose? J Comput Biol Med. 2012; 42: 164–70p.

Steven M.K., Stanley. Spectrum Analysis-A Modern Perspective. Proceeding of the IEEE. 1981; 69(11):

Ramseur J.T. Design, Evaluation, and Application of Heart Rate Variability Analysis Software RHVAS. Ph.D. Thesis. 2010.

Wacker M., Witte H.. Time-Frequency Techniques in Biomedical signal Analysis. A Tutorial Review of Similarities and Differences. 2013; 52: 279–96p.

Witte H, Ungureanu M, Ligges C, et al. Signal Informatics as an Advanced Integrative Concept in the Framework of Medical Informatics: New Trends Demonstrated by Examples Derived from Neuroscience. Methods Inf Med. 2009; 48: 18–28p.

Boashash B. Time-Frequency Signal Analysis. Methods and Applications. Melbourne: Longman Cheshire. 1992.

Novak P, Novak V. Time/Frequency Mapping of the Heart Rate, Blood Pressure and Respiratory Signals. Med Bio Eng Comp. 1993; 31: 103–110p.

Rioul O, Vetterli M. Wavelets and Signal Processing. IEEE Signal Process Mag. 1991; 8: 14–38p.

Bruns A. Fourier, Hilbert and Wavelet-Based Signal Analysis: Are They Really Different Approaches. Neurosci Method. 2004; 137: 321–32p.

Auger F., Flandrin P., Goncalves P., et al. Time-Frequency Toolbox. For Use with MATLAB. 1995 http://wwwnongnu.org/tftb tutorial pdf.

Young R. Wavelet Theory and Its Applications. Kluwer Academic. 1993.

Assous S., Boashash B. Evaluation of the Modified S-Transform for Time-Frequency Synchrony Analysis and Source Localization. EURASIP J Adv Signal Process. 2012; 49: 1687–6180p.

Lei Y., Lin J., He Z., et al. A Review on Empirical Mod Decomposition in Fault Diagnosis of Rotating Machinery. J Mech Syst Signal Process. 2013; 35: 108–26p.

Warlar R., Eswaran C. Integer Coefficient Band Pass Filter for the Simultaneous Removal of Baseline Wander, 50 Hz and 100 Hz Interference from the ECG. Med Biol Eng Comput. 1991; 29: 333–6p.

Tompkins J.W. Bio Medical Signal Processing. Book Phi Publisher.

Pan J., Tompkins W.J. A Real-Time QRS Detection Algorithm. IEEE Trans Biomed Eng. 1985; 32: 230–6p.

Mitove I.P. A Method for Assessment and Processing of Bio Medical Signals Containing Trend and Periodic Components. Med Eng Phys. 1998; 20: 660–8p.

Hash B.B. Time-Frequency Signal Analysis. Methods and Applications. Melbourne: Longman Cheshire. 1992.

Stockwell R.G. Why Use the S-Transform? Fields Institute Communications. 1991.

Wang Y. H. The Tutorial: S Transform. National Taiwan University, Taipei, Taiwan, ROC.

Stockwell R.G. Localization of the Complex Spectrum: The S Transform. IEEE Trans Signal Process. 1996; 44: 998–1001p.

Fausta O., Acharyaa U.R., Molinarib F. Linear and Non-Linear Analysis of Cardiac Health in Diabetic Subjects. Biomed Signal Process Control. 2012; 7: 295–302p.

Faust O., Bairy M.G. Nonlinear Analysis of Physiological Signals: A Review. J Mech Med Biol. 2012; 12: 1–20p.

Faust O., Prasad V.R., Swapna G., et al. Comprehensive Analysis of Normal and Diabetic Heart Rate Signals: A Review. J Mech Med Biol. 2013; 1: 405–8p.

Faust O., Acharya U.R., Krishnan U.S., et al. Analysis of Cardiac Signals using Spatial Filling Index and Time-Frequency Domain. Biomed Eng. 2004; 3: 1–30p.

Acharya U.R., Krishnan U.S., Min L. Automated Identification of Normal and Diabetes Hear Rate Signals Using Nonlinear Measures. J Comput Biol Med. 2013; 42: 1523–1529p.

Stock well R.G. A Basis for Efficient Representation of the S-Transform. J Digit Signal Process. 2006; 1: 4–6p.




DOI: https://doi.org/10.37628/jdcas.v1i2.91

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