An improved windowing technique for heart rate variability power spectrum estimation

References

• Mehta, S.S., Saxena, S.C., and Verma, H.K., 1997, Computer-aided interpretation of ECG for diagnostics. International Journal of Systems Science, 27, 43–58.
   Google Scholar
• Kulkarni, P.K., Vinod, K., and Verma, H.K., 1997, Diagnostic acceptability of FFT-based ECG data compression. Journal of Medical Engineering & Technology, 21, 185 — 189.
   Google Scholar
• Kulkarni, P.K., Vinod, K., and Verma, H.K., 1997, ECG data compression using fast Walsh transform and its clinical acceptability. International Journal of Systems Science, 28, 831 — 836.
   Google Scholar
• Saxena, S.C., Sharma, A., and Chaudhary, S.C., 1997, Data compression and feature extraction of ECG signals. International Journal of Systems Science, 28, 483–498.
   Web of Science ®Google Scholar
• Saxena, S.C., Vinod, K., and Hamde, ST., 2002, Feature extraction from ECG signals using wavelet transforms for disease diagnostics. International Journal of Systems Science, 33, 1073— 1085.
   Google Scholar
• Rompelman, O., Snijders, J.B.I.M., and Spronsen, C.J., 1982, The measurement of heart rate variability spectra with the help of a personal computer. IEEE Transactions on Biomedical Engineering, BME-29, 503 — 510.
   Google Scholar
• Task Force of the European Society of Cardiology, and the North American Society of Pacing and Electrophysiology, 1996, Heart rate variability — standards of measurement, physiological interpretation and clinical use. European Heart Journal, 17, 354–381.
   PubMed Web of Science ®Google Scholar
• Malik, M., 1998, Heart rate variability. Current Opinion in Cardiology, 13, 36–44.
   PubMedGoogle Scholar
• Kitney, RI., and Rompelman, O. (Eds), 1980, The Study of Heart Rate Variability (Oxford: Clarendon Press).
   Google Scholar
• Sayers, B., 1973, Analysis of heart rate variability. Ergonomics, 16, 17–32.
   PubMed Web of Science ®Google Scholar
• Kitney, RI., and Rompelman, O. (Eds), 1987, The Beat-by-Beat Investigation of Cardiovascular Function (Oxford: Clarendon Press).
   Google Scholar
• Malik, M., and Camm, A. J. (Eds), 1995, Heart Rate Variability (Armonk, NY: Futura Publishing).
   Google Scholar
• Akselrod, S., Gordon, D., Ubel, F.A., Shanon, S.C., Barger, A. C., and Cohen, R.J., 1981, Power spectrum analysis of heart rate fluctuation: A quantitative probe of beat-to-beat cardiovascular control. Science, 213, 220–222.
   PubMed Web of Science ®Google Scholar
• Baselli, G., Cerutti, S., Civardi, S., Lombardi, F., Malliani, A., Merri, M., Pagani, M., and Rizzo, G., 1986, Heart rate variability signal processing: A quantitative approach as an aid to diagnosis in cardiovascular pathologies. International Journal of Bio-Medical Computing, 20, 51 — 70.
   Google Scholar
• Sosnowski, M., Macfarlane, P.W., Czyz, Z., Skrzypek-Wanha, J., Boczkowska-Gaik, E., and Tendera, M., 2002, Age-adjustment of HRV measures and its prognostic value for risk assessment in patients late after myocardial infarction. International Journal of Cardiology, 86, 249–258.
   Google Scholar
• Sosnowski, M., Latif, S., Clark, E., Tendera, M., and Macfarlane, P.W., 1999, A new index of heart rate variability. European Heart Journal, 20 (Abstr. Suppl.), 335.
   Google Scholar
• Malpas, S.C., 2002, Neural influences on cardiovascular variability: Possibilities and pitfalls. American Journal of Physiology Heart Circulation Physiology, 282, H6–H20.
   Google Scholar
• Kobayashi, M., and Musha, T., 1982, 1/f fluctuation of heart beat period. IEEE Transactions on Biomedical Engineering, BME-29, 456–457.
   PubMed Web of Science ®Google Scholar
• Kamath, MV., and Fallen, EL., 1993, Power spectral analysis of heart rate variability: A noninvasive signature of cardiac autonomic function. Critical Reviews in Biomedical Engineering, 21, 245–311.
   PubMed Web of Science ®Google Scholar
• Wootton, R., and Craig, J. (Eds), 1999, Introduction to Telemedicine (London, UK: The Royal Society of Medicine Press).
   Google Scholar
• Kulkarni, P.K., Vinod, K., and Verma, H.K., 1997, Direct data compression techniques for ECG signals: Effect of sampling frequency on performance. International Journal of Systems Science, 28, 217–228.
   Web of Science ®Google Scholar
• Saxena, S.C., Sharma, A., and Chaudhary, S.C., 1997, Data compression and feature extraction of ECG signals. International Journal of Systems Science, 28, 483–498.
   Web of Science ®Google Scholar
• Kulkarni, P.K., Vinod, K., and Verma, H.K., 1997, Diagnostic acceptability of FFT-based ECG data compression. Journal of Medical Engineering & Technology, 21, 185–189.
   PubMed Web of Science ®Google Scholar
• Kulkarni, P.K., Vinod, K., and Verma, H.K., 1997, ECG data compression using fast Walsh transform and its clinical acceptability. International Journal of Systems Science, 28, 831–836.
   Web of Science ®Google Scholar
• Saxena, S.C., Vinod, K., and Hamde, ST., 2000, ECG data compression using non-redundant templates. IETE Technical Review, 17, 299–310.
   Web of Science ®Google Scholar
• Rompelman, O., Coenen, A.J.R.M., and Kitney, R.Y., 1977, Measurement of heart-rate variability (Part 1): Comparative study of heart-rate variability analysis methods. Medical & Biological Engineering & Computing, 15, 233–239.
   PubMed Web of Science ®Google Scholar
• Karemaker, J.M., 1997, Analysis of blood pressure and heart rate variability - theoretical considerations. In P.A. Low (Ed.), Clinical Autonomic Disorders (Philadelphia: Lippineon-Raven Publishers), pp. 309–322.
   Google Scholar
• Vijaya, G., Vinod, K., and Verma, H.K., 1998, ANN-based QRS-complex analysis of ECG. Journal of Medical Engineering & Technology, 22, 160–167.
   PubMed Web of Science ®Google Scholar
• Vijaya, G., Vinod, K., and Verma, H.K., 1997, Artificial neural network based wave complex detection in electrocardiograms. International Journal of Systems Science, 28, 125–132.
   Web of Science ®Google Scholar
• Saxena, S.C., Vinod, K., and Hamde, ST., 2002, QRS detection using new wavelets. Journal of Medical Engineering & Technology, 26, 7–15.
   PubMedGoogle Scholar
• Rangayyan, R.M., 2002, Biomedical Signal Analysis: A case study approach (New York, NY: Wiley and IEEE Press).
   Google Scholar
• Oppenheim, A.V., and Schafer, R.W., 1975, Digital Signal Processing (Englewood Cliffs NJ: Prentice-Hall).
   Google Scholar
• Keselbrener, L., and Akselrod, S., 1996, Selective discrete Fourier transform algorithm for time-frequency analysis: Method and application on simulated and cardiovascular signals. IEEE Transac-tions on Biomedical Engineering, 43, 789–802.
   PubMed Web of Science ®Google Scholar
• Singh, D., Vinod, K., Saxena, S.C., and Deepak, K.K., 2004, Effects of RR segment duration on HRV spectrum estimation. Physiological Measurement, 25, 721–735.
   PubMed Web of Science ®Google Scholar
• Ifeachor, E.C., and Jervis, B.W., 2002, Digital Signal Processing: A Practical Approach, 2nd edn (Delhi: Pearson Education Asia).
   Google Scholar
• Jervis, B.W., Coelho, M., and Morgan, G.W., 1989, Spectral analysis of EEG responses. Medical & Biological Engineering & Computing, 27, 230–238.
   PubMed Web of Science ®Google Scholar
• Singh, D., Vinod, K., and Saxena, S.C., 2004, Sampling frequency of the RR interval time-series for spectral analysis of the heart rate variability. Journal of Medical Engineering & Technology, accepted January 2004, to appear.
   Google Scholar
• Cerutti, S., Bianchi, AM., and Mainardi, L.T., 1995, Spectral analysis of the heart rate variability. In M. Malik and A.J. Camm (Eds), Heart Rate Variability (Armonk, NY: Futura Publishing), pp. 63–74.
   Google Scholar