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2016 | OriginalPaper | Chapter

2. State of the Art of Modelling and Simulation of the Physiological Systems

Author : Yar M. Mughal (Yar Muhammad)

Published in: A Parametric Framework for Modelling of Bioelectrical Signals

Publisher: Springer Singapore

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Abstract

This chapter reviews the physiology of the cardiovascular system in order to understand its main mechanisms and parameters, which are of interest in this work. This chapter also describes other researchers’ approaches to developing cardiovascular system models as well as three simulation examples, namely (a) a cardiovascular simulator (“CVSim”), (b) a software tool for analysing breathing-related errors in transthoracic electrical bio-impedance spectroscopy measurements, and (c) simulation of lung edema in impedance cardiography.

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previous chapter Introduction and Motivation

next chapter Proposed Novel Generic Framework for Modelling the Bioelectrical Information

The medulla oblongata is the lower half of the brainstem, which is continuous with the spinal cord, the upper half being the pons. It is mostly related to the medulla. The medulla covers the cardiac, respiratory, vomiting, and vasomotor centre, and hence deals with the autonomic (involuntary) functions of heart rate, breathing, and blood pressure.

The vasomotor centre (VMC) is a part of the medulla oblongata, which regulates the blood pressure and other homeostatic processes.

The BISS acronym is also used by Andrei Krivoshei (a researcher at Tallinn University of Technology, Estonia) in his published paper, “A Bio-Impedance Signal Synthesiser (BISS) for Testing of an Adaptive Filtering System” (Krivoshei 2006)). In his work, BISS stands for Bio-Impedance Signal Synthesizer . In this work, BISS stands for Bio-Impedance Signal Simulator.

Abtahi, F. et al.: Software tool for analysis of breathing-related errors in transthoracic electrical bioimpedance spectroscopy measurements. J. Phys. (Conference Series) 407, 012028. http://www.scopus.com/inward/record.url?eid=2-s2.0-84874095138&partnerID=tZOtx3y1 (2012)

Baker, K., Hill, D., Pale, T.: Comparison of several pulse-pressure tech. for monitoring stroke volume. Med. Biol. Eng. 12, 81–88 (1974)CrossRef

Bianco, C.: How Your Heart Works – How Stuff Works. http://health.howstuffworks.com/human-body/systems/circulatory/heart.htm (2014). Accessed 4 Dec 2014

Campbell, K., et al.: A pulsatile cardiovascular computer model for teaching heart-blood vessel interaction. Physiologist 25(3), 155–162 (1982)

Chen, X., et al.: Estimation of the total peripheral resistance baroreflex impulse response from spontaneous hemodynamic variability. Am. J. Physiol. 294(1), 293–301 (2008)

Cotter, G., et al.: Impedance cardiography revisited. Physiol. Meas. 27, 817–827 (2006)CrossRef

Deborah, R., Alvater, R.: Impedance Cardiography Mentor Resource Guide (2002)

Defares, J., Osbome, J., Hara, H.: Theoretical synthesis of the cardiovascular system. Study I: the controlled system. Acta. Physiol. Pharm. Neerl. 12, 189–265 (1963)

Franz, M.R. et al.: Electrical and mechanical restitution of the human heart at different rates of stimulation. Circ. Res. 53(6), 815–822 (1983). http://circres.ahajournals.org/cgi/doi/10.1161/01.RES.53.6.815

Grimnes, S., Martinsen, O.G.: Bioimpedance and Bioelectricity Basics. http://www.amazon.com/Bioimpedance-Bioelectricity-Basics-Third-Edition/dp/0124114709/ref=dp_ob_image_bk (2014). Accessed 26 Nov 2014

Grodins, F.S.: Integrative cardiovascular physiology: a mathematical synthesis of cardiac and blood vessel hemodynamics. Q. Rev. Biol. 34(2), 93–116 (1959)CrossRef

Harrub, B.: The Unevolvable Circulatory System. http://apologeticspress.org/APContent.aspx?category=12&article=980 (2005). Accessed 18 Feb 2015

Heldt, T. et al.: CVSim: an open-source cardiovascular simulator for teaching and research. The Open Pacing, Electrophysiol. Ther. J. 3, 45–54 (2010). Available at: http://physionet.incor.usp.br/physiotools/cvsim/45TOPETJ.pdf [Accessed November 16, 2014]

Jurjević, M. et al.: Mechanical ventilation in chronic obstructive pulmonary disease patients, noninvasive vs. invasive method (randomized prospective study). Collegium Antropologicum 33(3), 791–797 (2009). http://www.ncbi.nlm.nih.gov/pubmed/19860105. Accessed 25 Nov 2014

Kappel, F., Peer, R.O.: A mathematical model for fundamental regulation processes in the cardiovascular system. J. Math. Biol. 31(6), 611–631 (1993). http://link.springer.com/10.1007/BF00161201. Accessed 4 Dec 2014

Kappel, F.: Modeling the dynamics of the cardiovascular-respiratory system (CVRS) in humans, a survey. Math. Model. Nat. Phenom. 7(5), 65–77 (2012). http://www.mmnp-journal.org/10.1051/mmnp/20127506. Accessed 4 Dec 2014

Karnegis, Y., Kubicek, W.: Physiological correlates of the cardiac thoracic impedance waveform. Am. Heart J. 79, 519–523 (1970)CrossRef

Katz, S., et al.: Computer simulation in the physiology student laboratory. Physiologist 21(6), 41–44 (1978)

Kauppinen, P., Hyttinen, J., Malmivuo, J.: Sensitivity distributions of impedance cardiography using band and spot electrodes analyzed by a three-dimensional computer model. Ann. Biomed. Eng. 26, 694–702 (1998)CrossRef

Kauppinen, P.K., et al.: Lead field theoretical approach in bioimpedance measurements: towards more controlled measurement sensitivity. Ann. N. Y. Acad. Sci. 873, 135–142 (1999)CrossRef

Kenny, T., Tidy, C.: Electrocardiogram (ECG) | Health | Patient.co.uk. http://www.patient.co.uk/health/electrocardiogram-ecg (2012). Accessed 28 Nov 2014

Kersulyte, G., Navickas, Z., Raudonis, V.: Investigation of complexity of extraction accuracy modeling cardio signals in two ways. In: Proceedings of the 5th IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS’2009, pp. 462–467 (2009)

Kohl, P., Sachs, F., Franz, M.R.: Cardiac Mechano-Electric Coupling and Arrhythmias. Oxford University Press. http://books.google.com/books?id=AgoBCHptrFYC&pgis=1 (2011). Accessed 26 Nov 2014

Krivošei, A.: Model Based Method for Adaptive Decomposition of the Thoracic Bio-impedance Variations into Cardiac and Respiratory Components. Ph.D Thesis. University of Technology, Tallinn (2009)

Krivoshei, A.: A Bio-Impedance signal synthesiser (BISS) for testing of an adaptive filtering system. In: 2006 International Biennial Baltic Electronics Conference. IEEE, pp. 1–4. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4100325 (2006). Accessed 13 Nov 2014

Kubicek, W., Kottke, F., Ramos, M.: The Minnesota impedance cardiograph-Theory & appl. Biomed. Eng. 9, 410–416 (1974)

Lamberts, R., Visser, K., Zijlstra, W.: Impedance Cardiography (1984)

Lu, Z., Mukkamala, R.: Monitoring left ventricular contractility from respiratory-induced blood pressure variability. Comput. Cardiol. 31, 705–708 (2004)

Lu, Z., Mukkamala, R.: Non-invasive monitoring of left ventricular contractility and ventilatory mechanics. In: 27th Annual Conference of the IEEE Engineering in Medicine and Biology Society. pp. 7636–7639 (2005)

Malmivuo, J., Plonsey, R: Bioelectromagnetism - Principles and Applications of Bioelectric and Biomagnetic Fields. Oxford University Press (1995)

Matušek, A., Provazník, I., Fontecave-Jallon, J.: Modelling of Impedance Cardiac Signals (2012)

Mohapatra, S.: Noninvasive Cardiovascular Monitoring of Electrical Impedance Technique, London (1981)

Mohapatra, S., 1988. Impedance cardiography. In: Encyclopedia of Medical Devices and Instrument. Wiley, New York

Mughal, Y.M.: Conversation with Paul Annus, Tallinn University of Technology (2012)

Mughal, Y.M.: Decomposing of Cardiac and Respiratory Signals from Electrical Bio-impedance Data Using Filtering Method. In: Y.-T. Zhang, ed., Cham: Springer International Publishing. Available at: http://link.springer.com/10.1007/978-3-319-03005-0 (2014). Accessed 12 Nov 2014

Mughal, Y.M., Krivoshei, A., Annus, P.: Separation of cardiac and respiratory components from the electrical bio-impedance signal using PCA and fast ICA. In: International Conference on Control Engineering & Information Technology (CEIT’13). Sousse, Tunisia, pp. 153–156 (2013). http://arxiv.org/abs/1307.0915, Accessed 12 Nov 2014

Mughal, Y.M. et al.: An overview of the impedance models of the thorax and the origin of the impedance cardiography signal and modeling of the impedance signals. In: 2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES 2014) (2014)

Mughal, Y.M. et al.: Development of a bio-impedance signal simulator on the basis of the regression based model of the cardiac and respiratory impedance signals. In: Mindedal, H., Persson, M., (eds.) 16th Nordic-Baltic Conference on Biomedical Engineering. IFMBE Proceedings, Springer International Publishing, Gothenburg, pp. 92–95 (2015). http://link.springer.com/10.1007/978-3-319-12967-9, Accessed 12 Nov 2014

Mukkamala, R., Cohen, R.: A forward model-based validation of cardiovascular system identification. Am. J. Physiol. 281(6), 2714–2730 (2001)

Mukkamala, R., Toska, K., Cohen, R.: Noninvasive identification of the total peripheral resistance baroreflex. Am. J. Physiol. 284(3), 947–959 (2003)

Parati, G. et al.: European society of hypertension guidelines for blood pressure monitoring at home: a summary report of the second international consensus conference on home blood pressure monitoring. J Hypertens. 26(8), 1505–1526. http://www.ncbi.nlm.nih.gov/pubmed/18622223 (2008). Accessed 26 Nov 2014

Patterson, R.: Source of the thoracic cardiogenic electrical impedance signal as determined by a model. Med. Biol. Eng. Comput 23, 411–417 (1985)CrossRef

Patterson, R.: Impedance cardiography: what is the source of the signal? In: International Conference on Electrical Bioimpedance, pp. 1–4 (2010)

Patterson, R., Wang, L., Weigh, Mc: Impedance cardiography: The failure of sternal electrodes to predict changes in stroke volume. Biol. Psychol. 36, 33–41 (1993)CrossRef

Patterson, S.W., Piper, H., Starling, E.H.: The regulation of the heart beat. J. Physiol. 48(6), 465–513 (1914). http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1420509&tool=pmcentrez&rendertype=abstract. Accessed 4 Dec 2014

Penny, B.: Theory and cardiac applications of electrical impedance measurements. CRC Crit. Rev. Bioeng 13, 227–281 (1986)

Rosenberger, E.: The Difference between Invasive and Noninvasive Procedures. http://www.sciences360.com/index.php/the-difference-between-invasive-and-noninvasive-procedures-14048/ (2009). Accessed 26 Nov 2014

Sakamoto, K., Kania, H.: Electrical characteristics of flowing blood. IEEE Trans. Biomed. Eng. 26, 686–695 (1979)CrossRef

Sakamoto, K. et al.: Problems of impedance cardiography. Med. Biol. Eng. Comput. 17(6), 697–709 (1979). http://www.ncbi.nlm.nih.gov/pubmed/317910. Accessed 17 Jan 2015

Santos, N. et al.: Opto-electronic plethysmography: noninvasive and accurate measurement of the volume of the chest wall and its different thoraco-abdominal compartments, pp. 147–150 (2013)

Solà, J. et al.: Non-invasive monitoring of central blood pressure by electrical impedance tomography: first experimental evidence. Med. Biol. Eng. Comput. 49(4), 409–15 (2011). http://www.ncbi.nlm.nih.gov/pubmed/21404079. Accessed 20 Nov 2014

Sörnmo, L., Laguna, P.: Model Based Method for Adaptive Decomposition of the Thoracic Bio-impedance Variations into Cardiac and Respiratory Components. Elsevier Academic Press (2005)

Soudon, P., Steens, M., Toussaint, M.: A comparison of invasive versus noninvasive full-time mechanical ventilation in Duchenne muscular dystrophy. Chronic Respir. Dis. 5(2), 87–93 (2008). http://www.ncbi.nlm.nih.gov/pubmed/18539722. Accessed 25 Nov 2014

Sunagawa, K., Sagawa, K.: Models of ventricular contraction based on time-varying elastance. Crit. Rev. Biomed. Eng. 7(3), 193228 (1982)

Thompson, F., Joekes, A.: Thoracic impedance cardiodynamic assessment: validation in clinical use, London (1981)

Timischl, S.: A global model for the cardiovascular and respiratory system. Karl-Franzens University of Graz. http://staff.technikum-wien.at/~teschl/diss.pdf (1998)

Trolla, J., Vedru, J.: On the safety of foucault cardiography. In: XI International Conference Electrical Bio-impedance. Oslo, pp. 649–652 (2001)

Ulbrich, M., et al.: Simulation of lung edema in impedance cardiography. Comput. Cardiol. 39(1), 33–36 (2012)MathSciNet

Wang, L., Patterson, R.: Multiple source of the impedance cardiogram based on 3-D finite difference human thorax models. IEEE Trans. Biomed. Eng. 42(2), 141–148 (1995)CrossRef

Wang, L., Patterson, R., Raza, B.: Respiratory effects on cardiac related impedance indices measured under voluntary cardio-respiratory synchronization. Med. Biol. Eng Comput. 29, 505–510 (1991)CrossRef

Wittoe, D, Kottke, F.: The origin of cardiogenic changes in thoracic electrical impedance (del Z). In: Federation Proceedings (1967)

Woltjer, H.H., Bogaard, H.J., de Vries, P.M.: The technique of impedance cardiography. Eur. Heart J. 18, 1396–1403 (1997)CrossRef

Wu, H. et al.: Three dimensional electrical impedance tomography in thorax complete model. In: Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2008, pp. 466–469 (2008)

Xu, D., et al.: Improved pulse transit time estimation by system identification analysis of proximal and distal arterial waveforms. AJP: Heart Circulatory Physiol. 301, H1389–H1395 (2011)

Title: State of the Art of Modelling and Simulation of the Physiological Systems
Author: Yar M. Mughal (Yar Muhammad)
Publisher: Springer Singapore
Book: A Parametric Framework for Modelling of Bioelectrical Signals
Print ISBN: 978-981-287-968-4

Electronic ISBN: 978-981-287-969-1

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-981-287-969-1_2