External Info

This is an introductory course in biomedical signal and image processing. Topics include: biopotential generation; biosignal detection using metal electrodes; electrocardiogram; amplifiers and filter design for biosignal recording; and design considerations; 2D and 3D image formation; fluoroscopy, ultrasound, computed tomography, and magnetic resonance imaging; spatial and frequency‐domain filtering and feature extraction; applications in diagnostics, therapeutics, and interventions.

Academic Units: Mathematics 0/ Natural Sciences 9/ Complementary Studies 0/ Engineering Science 18 / Engineering Design 9

COREQUISITE(S): ELEC 323 or permission of the instructor

This course is designed for learners with some background in analog signal processing. 

Course Learning Outcomes (CLOs)

By the end of this course, students should be able to:

  • CLO-I.1: Explain image characteristics and how they are related image quality (knowledge base; eng sci)
  • CLO-I.2: Explain how medical images are obtained for a number of medical imaging technologies (knowledge base; nat sci)
  • CLO-I.3:  Recognize and explain how image processing tools are applied to medical images (knowledge base; eng sci)
  • CLO-I.4: Using appropriate processing tools, analyze and extract information from biological signal and/or image data (problem analysis; eng sci)  
  • CLO-S.1: Describe the generation of biopotentials and the characteristics of the major biological signals (knowledge base; nat sci)
  • CLO-S.2: Describe how the ECG is generated and how it is related to the anatomy and function of the heart (knowledge base; nat sci)
  • CLO-S.3: Describe and perform standard ECG signal processing techniques, including artifact removal (problem analysis; eng sci)
  • CLO-S.4: Describe and perform advanced ECG signal processing, including heart rate variability analysis (problem analysis; eng sci)
  • CLO-S.5: Identify components of an instrumentation system for biosignal recording and describe how biosignals are detected using electrodes (knowledge base; eng sci)
Program learning outcomes (CEAB graduate attribute indicators)

ELEC 408 develops the Canadian Engineering Accreditation Board Graduate Attributes through the following four indicators:

  • A knowledge base for engineering
  • Problem analysis
  • Investigation
  • Individual and team work
  • Communication skills
Credit Breakdown

Lecture: 3
Lab: 0
Tutorial: 0

Academic Unit Breakdown

Mathematics 0
Natural Sciences 9
Complementary Studies 0
Engineering Science 18
Engineering Design 9

COREQUISITE(S): ELEC 323 or permission of the instructor