Autonomic Nervous System for Sympathetic and Parasympathetic for Cardiac Event Coherence

  • Noel G. Tavares
  • R. S. GadEmail author
  • A. M. Hernandez
  • Uday Kakodkar
  • G. M. Naik
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 768)


Human body physiology is regulated through the central neural control (CNS) which takes signal from the respiratory system and ambiance which signifies atmospheric pressure, temperature and various gases in the environment. The central nervous system then controls the metabolic control of various organs through the afferent nerves and the efferent nerves reflecting the various reflex of the organs back to the CNS, which regulates the cardiovascular system (CVS) for the stroke volume (SV) of the blood and heart rate (HR). The SV and HR collectively synthesize the cardiac output of the heart balancing the body for the coherence or non-coherence states. We have defined and simulated here in this paper the Neural Mass Model (NMM), which is one of the component which feeds the CNS and controls the cardiovascular system for the human blood pressure (ABP) and heart rate. We have defined and simulated arterial blood pressure model, i.e., Windkessel model; describing the arterial blood pressure for the particular input volume of the blood and ECG model for the computing heart rate and heart rate variability (HRV). The integration of CNS, Windkessel and EEG model has thrown light on some aspects of sympathetic and parasympathetics of ANS for further improvisation and experimentations.


ANS Neural mass Human blood pressure EEG HRV 


  1. 1.
    Wendling, F., Bartolomei, F., Mina, F., Huneau, C., Benquet, P.: Interictal spikes, fast ripples and seizures in partial epilepsies combining multi-level computational models with experimental data. Eur. J. Neurosci. 36(2), 21642177 (2012)CrossRefGoogle Scholar
  2. 2.
    Wendling, F., Bartolomei, F., Bellanger, J.J., Chauvel, P.: Epileptic fast activity can be explained by a model of impaired gabaergic dendritic inhibition. Eur. J. Neurosci. 15(9), 14991508 (2002)Google Scholar
  3. 3.
    Lopes da Silva, F.H., Hoeks, A., Smits, H., Zetterberg, L.H.: Model of brain rhythmic activity, the alpha rhythm of the thalamus. Kybernetik 15(1), 2737 (1974)Google Scholar
  4. 4.
    Freeman, W.J.: Models of the dynamics of neural populations. Electroencephalogr. Clin. Neurophysiol. Suppl. (34), 9–18 (1977)Google Scholar
  5. 5.
    Zavalgia, M., Cona, F., Ursino, M.: A neural mass model to simulate different rhythms in a cortical region. Comput. Intell. Neurosci. Hindawi 10 (2010)Google Scholar
  6. 6.
    Otto, F.: Die Grundform des arteriellen Pulses. Zeitung für Biologie 37, 483–586 (1899)Google Scholar
  7. 7.
    Wang, L., Xu, L., Zhou, S., Wang, H., Yao, Y., Hao, L., Li, B.N., Qi, L.: Design and implementation of a pulse wave generator based on Windkessel model using field programmable gate array technology. Biomed. Sig. Process. Control 36, 93–101 (2017)Google Scholar
  8. 8.
    Opthof, T.: The normal range and determinants of the intrinsic heart rate in man. Cardiovasc. Res. 45(1), 177–184 (2000)Google Scholar
  9. 9.
    McSharry, P.E., Clifford, G.D., Tarassenko, L., Smith, L.A.: A dynamical model for generating synthetic electrocardiogram signals. IEEE Trans. Biomed. Eng. 50(3) (2003)Google Scholar
  10. 10.
    Lewis, M. J., Short, A. L.: Autonomic nervous system control of the cardiovascular and respiratory systems in asthma. Respir. Med. 100(10), 1688–1705 (2006)Google Scholar
  11. 11.
    Shaffer, F., McCraty, R., Zarr, L.: A healthy heart is not a metronome: an integrative review of the heart’s anatomy and heart rate variability. Front. Psychol. 5, 1040 (2014)Google Scholar
  12. 12.
    Ursino, M.: Interaction between carotid baroregulation and the pulsating heart: a mathematical model. AMJ Physiol. 275(5), H1733–H1747 (1998)Google Scholar
  13. 13.
    McCraty, R., Shaffer, F.: Heart rate variability: new perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk. Glob. Adv. Health Med. 4(1), 46–61 (2015)Google Scholar
  14. 14.
    Jang, A., Hwang, S.-K., Padhye, N.S., Meininger, J.C.: Effects of cognitive behavior therapy on heart rate variability in young females with constipation-predominant irritable bowel syndrome: a parallel-group trial. J. Neurogastroenterol. Motil. 23(3), 435 (2017)Google Scholar
  15. 15.
    Sowder, E.: Restoration of vagal tone, “a possible mechanism for functional abdominal pain”. Appl. Psychophysiol. Biofeedback 35(3), 199–206 (2010)Google Scholar
  16. 16.
    Reardom, M., Malik, M.: Changes in heart rate variability with age. Pacing Clin. Electrophysiol. 19(11), 1863–1866 (1996)Google Scholar
  17. 17.
    Elsenbruch, S., Harnish, M.J.: Heart rate variability during waking and sleep in healthy males and females. Sleep 22(8), 1067–1071 (1999)Google Scholar
  18. 18.
    Cerutti, C., Barres, C., Paultre, C.: Baroreflex modulation of blood pressure and heart rate variabilities in rats: assessment by spectral analysis. Am. J. Physiol. 266(5), H1993–H2000 (1994)Google Scholar
  19. 19.
    Cacioppo, J.T., Berntson, G.G.: The affect system architecture and operating characteristics. Curr. Dir. Psychol. Sci. 8(5), 133–137 (1999)Google Scholar
  20. 20.
    Berntson, G.G.: Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology. 34(6), 623–648 (1997)Google Scholar
  21. 21.
    Billman, G.E.: The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance. Front. Physiol. 4, 26 (2013). PMC. Web. 29 (Nov 2017)Google Scholar
  22. 22.
    Taylor, S.: Tend and befriend. Biobehavioral bases of affiliation under stress, Curr. Dir. Psychol Sci. 15(6), 273–277 (2006)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Noel G. Tavares
    • 1
  • R. S. Gad
    • 1
    Email author
  • A. M. Hernandez
    • 2
  • Uday Kakodkar
    • 3
  • G. M. Naik
    • 1
  1. 1.Department of ElectronicsGoa UniversityTaleigao PlateauIndia
  2. 2.Bioinstrumentation and Clinical Engineering Research Group (GIBIC)Universidad de Antioquia in MedellínMedellínColombia
  3. 3.Pulmonary MedicineGoa Medical College and HospitalBambolimIndia

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