BIOE 205

BIOE 205 - Signals and Systems in Bioengineering

This is the course website for the Spring 2023 offering of BIOE 205 - Signals and Systems in Bioengineering. BIOE 205 focuses on learning mathematical models of signals & systems, specifically biological systems, as well as techniques for their analysis using tools like MATLAB & Simulink. Use the menu elements above to navigate through the website.

Course Information

Lecture Time: 1000 \(-\) 1050 hrs on MWF
Location: Room 4025 in Campus Instructional Facility

Instructor: Ivan T. Abraham
E-mail: itabrah2 at illinois dot edu
Office hours: Wednesdays 1300 - 1430 hrs in EVRT 2254 and via Zoom

Teaching Assistant: Peibo Xu
E-mail: peiboxu2 at illinois dot edu
Office hours: Thursdays 1400 - 1600 hrs in EVRT 3100 and via Zoom

Courses Assistants:

See detailed course schedule.

Catalog Description

Introduction to signals and linear systems with examples from biology and medicine. Linear systems and mathematical models of systems, including differential equations, convolution, Laplace transforms, Fourier series and transforms, and discrete representations. In class examples and coursework apply general techniques to problems in biological signal analysis, including circuits, enzyme kinematics, and physiological system analysis. Use of MATLAB and Simulink software to understand more complex systems.

Course Outcomes

By the end of class, students will be able to …

  1. Understand the concepts of systems and signal representations.

  2. Use different mathematical tools to model physical and biomedical/biological phenomena and systems (i.e., differential equations, convolution, and signal transforms).

  3. Apply linear systems methods (i.e., convolution, Fourier analysis, and Laplace analysis) to characterize these models and calculate analytical solutions.

  4. Approximate biomedical signals with mathematical functions.

  5. Convert between time-domain, frequency-domain, and Laplace-domain representations of biomedical signals & systems and understand what can be learned from the representation.

  6. Understand the limits of different models and signal representations.

  7. Use MATLAB/Python to find computational solutions to linear systems.


Click here to go to the course catalogs where you may register for the course.

CC BY-SA 4.0 Ivan Abraham. Last modified: January 19, 2023. Website built with Franklin.jl and the Julia programming language. Curious? See familiar examples.