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Doctoral Thesis Czech Technical University in Prague Faculty of Biomedical Engineering Doctoral Thesis June 2010 Michel Kana Czech Technical University in Prague Faculty of Biomedical Engineering Department of Biomedical Informatics MATHEMATICAL MODELS OF CARDIOVASCULAR CONTROL BY THE AUTONOMIC NERVOUS SYSTEM Doctoral Thesis Michel Kana Prague , June 2010 Ph.D. Program: Biomedical and Clinical Technology Supervisor: Prof. Ing. Ji ři Hol čík, CSc. II Abstract This thesis develops an integrated mathematical model for autonomic nervous system control on cardiovascular activity. As a working control system, with diverse feedback and feedforward loops interfering with each other, our integrative model is key to understand paradoxal phenomenon such as vagally-mediated tachycardia, fluctuation of sinoatrial rhythms on denervated heart, Mayer waves and tonic activity of sympathetic premotor pacemaker neurons. The model extensively covers cardiovascular neural pathways including a wide range of afferent sensory neurons, central processing by autonomic premotor neurons, efferent outputs via preganglionic and postganglionic autonomic neurons and dynamics of neurotransmitters at cardiovascular effectors organs. The results achieved in this work are challenging some established methods for assessing autonomic activity on the cardiovascular system, e.g. heart rate variability, blood pressure variability, baroreflex sensitivity and conventional mathematical models based on control theory. Most of these methods picture a reciprocal control of cardiac vagal and sympathetic nervous activity, and neglect simultaneous co-activation of both autonomic efferent branches. Furthermore they lack to integrate cardiovascular reflexes across their many levels of organization and therefore miss to exhibit emerging properties of the regulatory processes. We performed over 500 cardiovascular experiments using clinical autonomic tests on 72 subjects ranging from 11 to 82 years old and collected typical cardiovascular signals such as electrocardiogram, arterial pulse, arterial blood pressure, respiration pattern, galvanic skin response and skin temperature. Next to a statistical evaluation in the time and frequency domains, the data were especially used to validate the mathematical model by resolving a constrained optimization task. Results bring evidences supporting the hypothesis that Mayer waves result from a rhythmic sympathetic discharge of pacemaker-like sympathetic premotor neurons. Simulation also show that vagally-mediated tachycardia, observed during vagal maneuvers on some subjects could be related to the secretion of vasoactive neurotransmitters by the vagal nerve. We additionally identified model parameters for estimating the resting sympathetic and parasympathetic tone which are believed to be linked to some pathological states. Results show higher vagal tone on young subjects with a decreasing trend with aging, what agrees with the data from heart rate variability studies. Tonic sympathetic activity was found to possibly emerge from pacemaker premotor neurons, but also from activation of chemoreceptors to a lesser extent. We include a software package as practical work product of this thesis for clinical applications. Our web-based telemedicine platform offers features for connecting doctors with remote patients, including signal processing, statistical evaluation and messaging. We extended the infrastructure with the design of biofeedback solution that upgrades a common mobile phone with low-cost sensors for skin temperature and finger pulse measurements, as well as a software module for uploading and downloading medical information and cardiovascular signals through internet. In summary this thesis offers a software and hardware application that could be useful in a clinical environment and proposes an integrative model of cardiovascular control that might help for educational and research purposes. The thesis also opens perspectives for future work including validating the markers of autonomic tone provided by our model against data from experiments with pharmacological blockers and invasive neural activity recordings. III Abstract in Czech Tato práce pojednává o vývoji integrovaného matematického modelu řízení kardiovaskulární aktivity autonomním nervovým systémem. Vytvořený funkční model, využívající navzájem interferující řídicí mechanismy jak se zpětnou, tak i přímou vazbou, je klíčovým prostředkem k porozumění takových paradoxních jevů, jako jsou vagem zprostředkovaná tachykardie, kolísání sinoatriálního rytmu na denervovaném srdci, Mayerovy oscilace, nebo tonická aktivita sympatických premotorických pacemakerových neuronů. Model zahrnuje vliv mnohých neurokardiovaskulárních vedení, včetně velkého počtu aferentních senzorických nervových cest, centrálního zpracování pomocí autonomních premotorických neuronů, eferentních výstupů zprostředkovaných pregangliovými a postgangliovými nervovými vlákny i vliv dynamiky neurotransmiterů v kardiovaskulárních efektorech. Dosažené výsledky mohou být užitečné v diskuzi o některých klasických metodách hodnocení autonomní aktivity kardiovaskulární soustavy, jako jsou variabilita srdečního rytmu, variabilita krevního tlaku, baroreflexní senzitivita a konvenční matematické modely založené na teorii řízení. Nabízejí prostor pro další výzkumné aktivity, zejména při hodnocení markerů tonu autonomního nervového systému, stanovených pomocí vytvořeného modelu pro data pořízená při experimentech s farmakologickými blokátory, příp. s invazivně zaznamenávanou nervovou aktivitou. Abstract in French Cette thèse traite de l'élaboration d'un modèle mathématique intégré du contrôle exercé par le système nerveux autonome sur le système cardiovasculaire. Ce modèle représente le fonctionnement de divers mécanismes de régulation neurologique, interférant les uns avec les autres et est une clé pour comprendre des phénomènes paradoxaux, comme la tachycardie parasympathique, les fluctuations à haute-fréquence observées sur le nœud sino-auriculaire du cœur dénervé, les oscillations de Mayer, ou encore l'activité tonique des neurones sympathiques prémoteurs. Le modèle permet de simuler un grand nombre de voies neurales autonomes connues, y compris les voies neurales sensorielles afférentes, les voies neurales centrales autonomes, les sorties efférentes incluant les neurones pré-ganglionnaires et post- ganglionnaires, ainsi que la concentration des neurotransmetteurs au niveau des organes cardiovasculaires tels que ventricules, oreillettes, nœud sino-auriculaire, nœud auriculo- ventriculaire et vaisseaux sanguins. Les résultats obtenus mettent certaines méthodes classiques d'évaluation de l’activité du système nerveux autonome sur le système cardiovasculaire à l’épreuve, tels que la variabilité du rythme cardiaque, la variabilité de la tension artérielle, la sensibilité baroréflexe, et les modèles mathématiques conventionnelles basés sur la théorie du contrôle. Ce travail offre des possibilités de poursuivre les recherches, en particulier dans l'évaluation des marqueurs du système nerveux autonome à l'aide des données acquises dans des expériences utilisant des inhibiteurs pharmacologiques. IV Acknowledgment This work would have not been possible without Lucie, my lovely wife and Simon, my fantastic son. Lucie had so much patience with me along these years and never stopped encouraging me. Her affection was a real source of energy empowering my work. I am very thankful towards my dear dad and mum, Paul and Elise Kana who set the educational basis for scientific work since my childhood. My achievements are fruits of their constant support and prayers. This work fulfills one of their deepest wishes. I am paying one of the debts a Bamileke descendant has towards his parents. Special thanks to Helena Simonova and Petr Simon, my parents-in-law for their constant support as well as my sisters Rosette Detsi, Lydie Biandu, Hermine and Laurece Kana who were always giving me courage. I thank my whole big family, grand-pa, grand-ma, aunts, uncles, cousins from the Cameroonian side as well as my family from the Czech side, especially Jaroslava Dvorakova and Anna Tresnakova. I have special thoughts for my cousin, Sonia Zebaze, who will make an excellent medical doctor one day; and my grand-ma M’a Konza who always looks so beautiful and young. As I was still a baby, my uncle Dr. Michel Ngueti dedicated his PhD thesis to me, and wished to see me achieving greater challenges. I am very grateful for his great influence on my scientific thinking. This thesis wouldn’t be without an exceptional PhD supervisor. That’s the one who used to bring me back to the main road of success. I sincerely thank my PhD father, Prof. Ing. Jiri Holcik. This work has been officially reviewed by Prof. Richard Reilly and Doc. Ing. Milan Tysler. I thank them for the constructive feedback. I am very grateful for the strong scientific feedback provided by Doc. MUDr. RNDr. Petr Marsalek. I also thank Dr. Esther Tamm, Prof. Pavel Kucera and MUDr. Jan Wichterle for support and advices during my studies. The Department of Biomedical Informatics was hosting my research. I felt there at home thanks to the head of department, Dr. Zoltan Szabo. Thanks a lot to Dr. Jan Kauler for the good mood and help with biomedical sensors. I would also thank my colleague and friend Mgr. Radim Krupicka who accompanied me along my studies. I thank doc. Marcel Jirina for the good advices, especially about the artificial neural parts of this thesis. Special regards to Mrs. Lucie Kulhankova for helping out
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