Simulation and Modeling

Lecturer:

Tutor:

Supervisor:

Department of Control Engineering

Synopsis:

Modeling method in general and in biomedical engineering. Types of models, continuous and discrete time parametric models, linear and nonlinear formalization. Process of model creation, model identification and verification. Utilization of fuzzy logics and reasoning. Examples of electromechanical and acoustic analogies and models. Models of specific individual physiologic systems, and those of whole complex systems in biology and medicine, e.g. models of cellular and of physiological regulation. Model application in creation of artificial organs.

Requirements:

Syllabus of lectures:

1. Models of systems, their classification, formalization and model creation

2. Continuous time parametric models, linear and nonlinear, model analogy

3. Discrete time parametric models, linear and nonlinear, sampling period

4. Experimental parameters assessment, identification and model verification

5. Systems with spread parameters and their models

6. Possibility of using fuzzy logic models

7. Models based on neural networks

8. Chemical and pharmakokinetic modeling

9. Cellular regulation models

10. Population dynamics modeling

11. Neurocybernetics models

12. Models of respiratory regulation and baroreflex

13. Models of glycemi regulation and gastric acidity

14. Models of cardiovascular system and dependence of heart rate on physical load

Syllabus of tutorials:

1. Introduction to laboratory and software equipment, kinds of models

2. MATLAB programming package with SIMULINK

3. Control Toolbox and System Identification Toolbox for MATLAB

4. Data acquisition and real-time signal processing in Real Time Toolbox for MATLAB

5. Examples of electromechanical and acoustic models

6. Fuzzy Logic Toolbox for MATLAB - models examples

7. Neural Network Toolbox for MATLAB - models examples

8. Model of kidney function by heart pressure stabilization

9. Model of isometric contraction of skeletal muscle

10. Simulation with continuous and discrete models of population dynamics

11. Models of neuron and neural nets, Genesis system

12. Modeling of lung, brain compartmets and other tissues

13. Man-machine system behavior simulation

14. Stress modeling and simulation, its responses in psychosomatic quantities

Study Objective:

Study materials:

1. Karnoop, D.C., Margolis, D.L., Rosenberg, R.C.: System Dynamics: A Unified Approach. John Wiley, New York 1990

2. Jang, J.S.R., Sun, C.T., Mizutani E.: Neuro-fuzzy and Soft Computing, 1997. Prentice Hall

3. Biomedical Engineering - Handbook,1995, CRC Press, Inc

4. Biomedical Modeling and Simulation on PC, Springer - Verlag, New York, 1993

5. Ljung, L., Torkel, G.: Modeling of Dynamic Systems. Prentice Hall, Englewood Cliffs 1994

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Biomedical Engineering- structured studies (compulsory elective course)