Modeling and Simulation
Code  Completion  Credits  Range  Language 

A6M33MOS  Z,ZK  5  2P+2C  Czech 
 The course cannot be taken simultaneously with:
 Modeling and Simulation (BAM33MOS)
Simulation and Modeling (X35SIM)  The course is a substitute for:
 Simulation and Modeling (X35SIM)
 Lecturer:
 Tutor:
 Supervisor:
 Department of Cybernetics
 Synopsis:

The modelling techniques being frequently used in biomedical engineering and corresponding software tools: MatlabSimulink, Modelica. Techniques of modelling and processes associated with them. Types of models, continuous and discrete time models, linear and nonlinear models with lumped parameters, models and their implementation in program environment. Formalization and model creation for a selected system, its identification, verification and interpretation. Equilibrium states (homeostasis) and their inquiry by simulation. Models of open and feedback systems. Use of fuzzyneuronal models in biomedicine. Models of separate systems and whole constellations being defined in biomedical engineering. Models of cellular and physiological control, population models. Application of models for artificial organs production.
 Requirements:

No prerequisities.
 Syllabus of lectures:

1.Mathematical modelling in BMI  examples of composition of physiological systems models.
2.Static analysis of physiological systems and processes. Examples: cardiac output control, glycemy control, acidobasic equilibrium control, chemical control of ventilation.
3.Timedomain analysis of linear regulation processes in physiological systems. Linearized model of breathing mechanics, dynamics of the neuromuscular reflex arc.
4.Frequencydomain analysis of linear regulation processes in physiological systems. Frequency response of circulation control and glycemy control models.
5.Methods of physiological control systems identification, experiments with Starling heartlungs preparate. Kaov's experiments with crossed circulation, controlled perfusion of brain for central and peripheral chemoreceptors separation, galvanic clamp, pupilar reflex loop opening, rebreathing techniques. Minimal model of glucose control, identification of parameters of breathing regulation.
6.Physiological processes stability testing: analysis of pupilar reflex stability, CheyneStokes breathing model, homeostasis.
7.Optimization problems in biological systems: normal breathing pattern control, aortal pulse wave control, adaptive control of physiological variables adaptive attenuation of arterial PCO2 fluctuations.
8.Methods of nonlinear analysis of physiological regulation systems  heart arrhythmia modelling, periodic breathing with apnoea. Neuron dynamics models: HodgkinHuxley model, Bonhoeffervan der Pol model.
9.Description of complex dynamics in physiological control systems  spontaneous variability, logistics equation, neutrophile density control, cardiovascular variability model, circadian rhythms model. Sleep apnoea model.
10.Fuzzy modelling use and definition given incomplete information on physiological processes.
11.Modelling of physiological systems and processes by neural networks.
12.A review of models on the cell, organ and system levels. Discussion of its usability.
13.The structure and expandability of an interactive catalogue of biomedical models.
14.Reserve.
 Syllabus of tutorials:

An addition to regular demonstration of models during seminars each student will be given an individual exercise based on measurements on a biological object, processing of collected data, model design, identification, verification, and interpretation. Realtime mode of models might be required. Progress will be checked three times during the term. A necessary documentation should be submitted and the model should be presented to the fellow students. Exam grade will depend on activity points collected during the term as well as on the results of oral and written exams.
 Study Objective:

The goul of the course is to teach studentes modelling techniques being frequently used in biomedical engineering.
 Study materials:

[1] Jang, J.S.R., Sun, C.T., Mizutani E.: Neurofuzzy and Soft Computing, 1997. Prentice Hall.
[2] Biomedical Engineering  Handbook,1995, CRC Press, Inc.
[3] Biomedical Modeling and Simulation on PC, Springer  Verlag, New York, 1993.
[4] Murray, J.D.:Mathematical Biology I,II, Spatial Models and Biomedical Applicatios, Springer, 2002, 2003.
[5] Michael C. K. Kho: Physiological Control Systems. Analysis, Simulation and Estimation. IEE Press, New York, 2000, ISBN 0780334086.
[6] Hugh R. Wilson: Spikes, Decisions and Actions. Dynamical foundation of neuroscience. Oxford University Press, Oxford, 1999, ISBN 0198524307.
[7] Frank C. Hoppensteadt, Charles S. Peskin: Modeling and Simulation in Medicine and the Life Sciences. Springer 2000,ISBN 0387950729.
[8] Robert D. Strum, Donald E. Kirk: Contemporary Linear Systems using Matlab. PWS Publishing Company, Boston, 1999, ISBN: 0534947107.
[9] Keener,J Sneyd,J: Mathematical Physiology. Springer, New York, Berlin, 1998, ISBN 0387983813.
 Note:
 Further information:
 http://cw.felk.cvut.cz/doku.php/courses/a6m33mos/start
 No timetable has been prepared for this course
 The course is a part of the following study plans: