Time-frequency analysis of the heart rate variability during the Valsalva manoeuvre

References

• VAN RAVENSWAAG-ARTS, C. M., KoLLEE, L. A., HOPMAN, J. C., STOELINGA, G. B., and VAN GEIJT, H., 1993, Heart rate variability. Annals of Internal Medicine, 118, 436–444.
   Google Scholar
• BILLMAN, G. E., and DUJARDIN, J. P., 1990, Dynamic changes in cardiac vagal tone as measured by time series analysis. American Journal of Physiology, 258, H896–902.
   PubMedGoogle Scholar
• KATONA, P. G., and Jut, F., 1975, Respiratory sinus arrhythmia: noninvasive measure of parasympathetic car-diac control. Journal of Applied Physiology, 39, 801–805.
   PubMed Web of Science ®Google Scholar
• MALLIANI, A., PAGANI, M., LOMBARDI, F., and CERRUTTI, S., 1991, Cardiovascular neural regulation in the frequency domain. Circulation, 84, 482–510.
   PubMed Web of Science ®Google Scholar
• BOOTH, R. W., RYAN, J., MELLET, H., Swiss, E., and NETH, E., 1962, Hemodynamic changes associated with the Valsalva manoeuver in normal men and women. Journal of Laboratory & Clinical Medicine, 59, 275–285.
   Web of Science ®Google Scholar
• MANTISAARI, M., 1994, Hemodynamic reactions to circula-tory stress tests in patients with neurocirculatory dystonia. Scandinavian Journal of Clinical Laboratory Investigation, 44 (suppl 170), 1–112.
   Google Scholar
• PIHA, S. J., 1988, Cardiovascular autonomic function tests. Responses in healthy subjects and determination of the aged related reference values. Publications of the Social Insurance Institution, Finland, ML, 85, 1–148.
   Google Scholar
• SHARPEY-SCHAFER, E. P., 1955, Effects of Valsalva's man-oeuvre on the normal and failure circulation. British Medical Journal, 1, 693–695.
   PubMedGoogle Scholar
• ECKBERG, D. L., 1980, Parasympathetic cardiovascular control in human disease: a critical review of methods and results. American Journal of Physiology, 239, H581–593.
   Google Scholar
• KORNER, P. I., TONKIN, A. M., and UTHER, J. B., 1976, Reflex and mechanical circulatory effects of graded Valsalva manoeuvres in normal man. Journal of Applied Physiology, 40, 434–440.
   Web of Science ®Google Scholar
• HAKUMAKI, M. 0. K., WANG, B. C., SUNDET, W. D., and GOETZ, K. L., 1985, Aortic baroreceptor discharge during nonhypotensive hemorrage in anesthesized dogs. American Journal of Physiology, 249, H393–403.
   Google Scholar
• GOLDBERGER, A. L., and WEST, B. J., 1987, Fractals in physiology and medicine. Yale Journal of Biology and Medicine, 60, 421–435.
   PubMed Web of Science ®Google Scholar
• PAGANI, M., LOMBARDI, F., GUZZETTO, S., RIMOLDI, 0., FURLAN, R., PIZZINELLI, R., SANDRONE, G., MALFATTO, S., DELL'ORTO, S., PICCALUGA, E., TURIEL, M., BASELLI, G., CERUTTI, S., and MALLIANI, A., 1986, Power spectral analysis of the heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and con-scious dog. Circulation Research, 59, 178–193.
   Google Scholar
• SAUL, J. P., ALBRECHT, P., BERGER, R. D., and COHEN, R. J., 1988, Analysis of long term heart rate variability methods, 1/f scaling and implications. Computers in Cardiology, 14, 419–422.
   Google Scholar
• SAUL, J. P., 1990, Beat to beat variations of heart rate reflect modulation of cardiac autonomic outflow. News in Physio-logical Science, 5, 32–37.
   Google Scholar
• BUTLER„ G. C., YAMAMOTO, Y., XING, H. C., NORTHEY, D. R., and HUGHSON, R. L., 1993, Heart rate variability and fractal dimension during orthostatic challenges. Journal of Applied Physiology, 75, 2602–2612.
   Google Scholar
• AKSELROD, S., GORDON, D., MADWED, J. B., SNIDMAN, N. C., SHANNON, D. C., and COHEN, R. J., 1985, Hemodynamic regulation: investigation by spectral analysis. American Journal of Physiology, 249, H867–875.
   PubMed Web of Science ®Google Scholar
• POMERANZ, B., MACAULEY, R. J. B., CAUDILL, M. A., KUTZ, Y., ADAM, D., GORDON, D., KILBO RN, K. M., BERGER, A. C., SHANNON,D. C., COHEN, R. J., and BENSON, H., 1985, Assessment of autonomic function in h uman s byh eart rate spectralanalysis. American Journal of Physiology, 248, H 151–153.
   Google Scholar
• BASELLI, G., CERUTTI, S., CIVARDI, S., LIVERATI, D., LOMBARDI, F., MALLIANI, A., and PAGANI, M., 1986, Spectral and cross-spectral analysis of heart rate and arterial blood pressure variability signals. Computers and Biomedical Research, 19, 250–534.
   Google Scholar
• MALLIANI, A., PAGANI, M., and LOMBARDI, F., 1994, Physiology and clinical implications of variability of cardiovascular parameters with focus on heart rate and blood pressure. American Journal of Cardiology, 73, 3C–9C.
   Google Scholar
• BIGGER, T., FLEISS, J. L., ROLNITSKY, L. M., and STEINMAN, R. C., 1993, The ability of several short-term measures of RR variability to predict mortality after myocardial infarction. Circulation, 88, 927–934.
   PubMed Web of Science ®Google Scholar
• BIGGER, J. T., FLEISS, J. L., STEINMAN, R. C., ROLNITSKY, L. M., SCHNEIDER, W. J., and STEIN, P. K., 1995, RR variability in healthy, middle-aged persons compared with patients with chronic coronary heart disease or recent acute myocardial infarction. Circulation, 91, 1936–1943.
   PubMed Web of Science ®Google Scholar
• CASOLO, G. C., STRODER, P., SULLA, A., CHELUCCI, A., FRENI, A., and ZERAUSCHEK, M., 1995, Heart rate variability and functional severity of congestive heart failure secondary to coronary artery disease. European Heart Journal, 16, 360–367.
   Google Scholar
• KAY, S. M., and MARPLE, S. L., 1981, Spectrum analysis—a modern perspective. Proceedings of the IEEE, 69, 1380–1419.
   Web of Science ®Google Scholar
• POLA, S., MACERATA, A., EMDIN, M., and MARCHESI, C., 1996, Estimation of the power spectral density in nonstationary cardiovascular time series: assessing the role of the time—frequency representations. IEEE Transactions on Biomedical Engineering, 43, 46–59.
   PubMed Web of Science ®Google Scholar
• JAFFE, R., and FUNG, D., 1994, Constructing a heart-rate variability analysis system. Journal of Clinical Monitoring, 10, 45–58.
   Google Scholar
• KOBAYASHI, M., and MUSHA, T., 1982, 1/f fluctuations of heart beat period. IEEE Transactions on Biomedical Engineer-ing, 29, 456–457.
   PubMed Web of Science ®Google Scholar
• LIPSITZ, L. A., MIETUS, J., MOODY, G. B., and GOLDBERGER, A. L., 1990, Spectral characteristics of heart rate variability before and during postural title: relation to aging and risk of syncope. Circulation, 81, 1803–1810.
   PubMed Web of Science ®Google Scholar
• BUTLER, G. C., YAMAMOTO, Y, and HUGHSON, R., 1994, Heart rate variability to monitor autonomic nervous system activity during orthostatic stress. Journal of Clinical Pharma-cology, 34, 558–562.
   PubMed Web of Science ®Google Scholar
• MAYER-KRESS, G., YATES, F. E., BENTON, L., KEIDEL, M., TIRSCH, W., POPPL, S. J., and GEIST, K., 1988, Dimensional analysis of nonlinear oscillations in brain, heart and muscle. Mathematical Bioscience, 90, 155–182.
   Google Scholar
• CARRASCO, S. S., JIMENEZ, J. R., GONZALEZ, C. R., ROMAN, R. R., MEDINA, B. V., and AZPIROZ, L. J., 1995, Comparacibn del desempelio de tres técnicas de estimacibn espectralpara el anhlisis de la variabilidad de la frecuencia cardiaca. Rev ista Mexicana de Ingenieria Biom'edica, 16, 15–34.
   Google Scholar
• GAITAN, G. J., CARRASCO, S. S., and Goisizjat,Ez, C. R., 1998, Deteccibn de onda R por diferenciacibn estadistica del complejo QRS. Memorias del IV Simposio del Departamento de Ciencias de la Salud, UAM-Iztapalapa, p. 29.
   Google Scholar
• BERGER, R., AKSELROD, S., GORDON, D., and COHEN, R. J., 1986, An efficient algorithm for spectral analysis of heart rate variability. IEEE Transactions on Biomedical Engineering, 33, 900–904.
   PubMed Web of Science ®Google Scholar
• EL-JAUROUDI, A., REDFERN, M. S., CHAPARRO, L. F., and FURMAN, J. M., 1996, The application of time—frequency methods to analysis of postural sway. Proceedings of the IEEE, 84, 1312–1318.
   Google Scholar
• Guo, Z., DURAND, L. G., and LEE, H. C., 1994, The time—frequency distributions of non stationary signals based on a bessel kernel. IEEE Transactions on Signal Processing, 42, 1700–1707.
   Google Scholar
• WOOD, J. C., and BARRY, D. T., 1995, Time—frequency analysis of the first heart sound. IEEE Engineering in Medicine and Biology, 14, 144–151.
   Web of Science ®Google Scholar
• LIN, Z., and CHEN, ID., 1995, Comparison of three running spectral analysis methods for electrogastrographic signals. Medicine and Biology Engineering and Computing, 33, 596–604.
   PubMedGoogle Scholar
• WILLIAMS, W. J., ZAVERI, H. P., and SACKELLARES, C., 1995, Time—frequency analysis of electrophysiology signals in epilepsy. IEFF Engineering in Medicine and Biology, 14, 133–143.
   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 Transactions on Biomedical Engineering, 43, 789–802.
   PubMed Web of Science ®Google Scholar
• NOVAK, P., and NOVAK, V., 1993, Time—frequency mapping of the heart rate blood pressure and respiratory signals. Medical and Biological Engineering and Computing, 31, 103–110.
   PubMed Web of Science ®Google Scholar
• COHEN, L., 1995, Time Frequency Analysis (Engelwood Cliffs, NJ: Prentice Hall).
   Google Scholar
• Cum, H., and WILLIAMS, W. J., 1989, Improved time—frequency representation of multicomponent signals using exponential kernels. IEEE Transactions on Acoustic, Speech and Signal Processing, 37, 862–871.
   Google Scholar