University of Wisconsin Madison
Mathematical and Computer Modeling of Physiological Systems (E C E 461) Syllabus
Course Learning Outcomes
    Course Learning Outcome
  • 1
    Bringing together knowledge in physiology and modeling techniques, this course will develop the student's ability: To appreciate the value and application of physiological models
  • 2
    To understand the physiology of some vital organs
  • 3
    To understand the process of modeling dynamically varying physiological systems
  • 4
    To understand methods and techniques to analyze and synthesize dynamic models
  • 5
    To develop differential equations to describe the dynamic behavior of physiological systems
  • 6
    To simulate and visualize dynamic responses of physiological models using computers
  • 7
    To define and implement physiological models for education, research and product development
  • 8
    To solve and implement a modeling and design problem from inception to completion
Mathematical and Computer Modeling of Physiological Systems
E C E 461 ( 3 Credits )
Mathematical and computer modeling of physiological systems; principal emphasis on cardiovascular system and individual nerve cells; other topics include respiratory system and skeletal-muscle system; extensive use of 'hands-on' computer modeling using ACSL.
ECE 330 or cons inst
College: College of Engineering
Instructor Name
Instructor Campus Address
Contact Hours
Course Coordinator
Text book, title, author, and year
Mathematical and Computer Modeling of Physiological Systems, Vincent C. Rideout, Prentice-Hall, 1991.
Supplemental Materials
Required / Elective / Selected Elective
Selected Elective
ABET Program Outcomes Associated with this Course
Program Specific Student Outcomes
Brief List of Topics to be Covered

- Applications of mathematical & computer physiological models Fundamental principles, processes and tools in model development

- Analysis and synthesis of dynamic models

- Pressure-flow Model ; Cardiac and circulation dynamics; Lung mechanics;

- Model approximation and simplification ; Cardiovascular system (Lumped model; Linearization; Non-pulsatile)

- Gas exchange and transport model ; Oxygen and carbon dioxide exchange; Respiratory system

- Compartment Model ; Mass transport through diffusion and fluid flow

- Multiple Model ; Oxygen and Carbon dioxide transport, Inhaled anesthetic uptake and distribution; Renal system

- Interactive Large-scale Multiple Model ; Interaction between inhaled anesthetics and blood circulation

- Concentration/Population Equilibrium Model ; Enzyme reaction (Michaelis-Menton kinetics); Membrane resting and action potential (Nerst equation); Immune system

- Cable conduction model ; electrical conduction and Signal propagation in the nervous system

- Finite difference Model ; Heat flow and thermal regulation

- Finite element Model ; Cardiac Tissue

- Descriptive Quantitative Model ; Body fluid balance; Glucose-Insulin regulation;

- Feedback models ; Starling Law, Neural feedback (Baroreceptor loop, neuromuscular), thermal regulation

- Programming language ACSL and Matlab/Simulink/Visualization

- Survey of commercial and research in Virtual Physiological systems in medical education

Additional Information
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