Abstract
Herein, we make a theoretical effort to characterize the interplay of the main stimuli underlying the cardiac control. Based on the analysis of heartbeat intervals and using neural coding strategies, we investigate the hypothesis that information theoretic principles could be used to give insights to the strategy evolved to control the heart. This encodes the sympathetic and parasympathetic stimuli. As a result of analysis, we illustrate and emphasize the basic sources that might be attributed to control the heart rate based on the interplay of the autonomic tones.
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Vetter, R., Celka, P., Vesin, J.M., Thonet, G., Pruvot, E., Fromer, M., Scherrer, U., Bernardi, L.: Subband modeling of the human cardiovascular system: New insights into cardiovascular regulation. Annals of Biomed. Eng. 26, 293–307 (1998)
Baselli, G., Cerutti, S., Civardi, S., Malliani, A., Pagani, M.: Cardiovascular variability signals: Towards the identification of a closed-loop model of the neural control mechanisms. IEEE Trans. Biomed. Eng. 35(12), 1033–1046 (1988)
Chon, K.H., Mullen, T.J., Cohen, R.J.: A dual-input nonlinear system analysis of autonomic modulation of the heart rate. IEEE Trans. Biomed. Eng. 43(5), 530–544 (1996)
Wiklund, U., Akay, M., Niklasson, U.: Short-term analysis of heart-rate variability by adapated wavelet transforms. IEEE Eng. Med. and Biol. 16(5), 113–118 (1997)
Pola, S., Macerata, A., Emdin, M., Marchesi, C.: Estimation of the power spectral density in nonstationary cardiovascular time series: Assessing the role of the time-frequency representations (tfr). IEEE Trans. Biomed. Eng. 43(1), 46–59 (1996)
Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.K., Stanley, H.E.: PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23), e215–e220 (2000)
Wessel, N., Voss, A.: Renormalised Entropy: A New Method of Non-Linear Dynamics for the Analysis of Heart Rate Variability. Comp. Card. 93, 1043–1065 (1994)
Bell, A.J., Sejnowski, T.J.: The “Independent Components” of Natural Scenes are Edge Filters. Vision Res. 23, 3327–3338 (1997)
Akselrod, A., Gordon, A., Ubel, F.A., Shannon, D.C., Barger, A.C., Cohen, R.J.: Power Spectrum Analysis of Heart Rate Fluctuation: A Quantitative Quantitative Probe of Beat-to-Beat Cardiovascular Control. Science 213, 220–222 (1981)
Ivanov, P.C., Rosemblum, M.G., Peng, C.-K., Mietus, J., Havlin, S., Eugene, S.H., Goldberger, A.L.: Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis. Nature 383, 323–327 (1996)
Armour, A.J.: Cardiac neuronal hierarchy in health and disease. Am. J. Physiol. Regul. Integr. Comp. Physiol. 271, R262–R271 (2004)
Task Force of the ESC and the NASPE. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation 93, 1043–1065 (1996)
Berntson, G.G., Cacioppo, J.T.: Heart Rate Variability: A Neoroscientific Perspective for Further Studies. Card Electrophysiol Review 3, 279–282 (1999)
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Lucena, F., Brito, D.S., Barros, A.K., Ohnishi, N. (2009). An Analysis of the Autonomic Cardiac Activity by Reducing the Interplay between Sympathetic and Parasympathetic Information. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_21
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DOI: https://doi.org/10.1007/978-3-642-02490-0_21
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