Introduction To Biomedical Signal Processing

Course Objectives

The purpose of this course is to introduce students with the fundamentals of biomedical signal processing with particular emphasis on solving real world problems. This course applies knowledge of math, engineering and science to understand the principle of biomedical signal processing. It deals with the understanding on how to apply specific mathematical techniques to solve problems in the areas of biomedical signals. The topics include origins and characteristics; modelling medical signals and systems; interference, artefact and noise removal; waveform complexity and event detection; nonlinear methods in medical system identification; emerging techniques in medical signal processing. Through a series of focused active learning project activities using real-world signals, the course will provide opportunities to acquire in-depth knowledge of processing physiological data such as ECG, EEG, MEG, Ultrasound. The lectures will be accompanied by data analysis assignments using MATLAB.

Pre-requisites N/A

Learning Outcome

Course Topics

Textbook

Reference Book:

Analyzing Neural Time Series Data: Theory and Practice (2014, MIT Press) By Mike X Cohen

Introduction To Biomedical Engineering,Third Edition, By John D. Enderle, Joseph D. Bronzino

Make-up Policy

No make-up testes for the missed Term Examinations and Quizzes.

Distribution of Points

Attendance --- ---------------------- 10 %

Project/ Assignments------------------------------------------- 25%

Paper Summary -------------------------------------------- 10 %

Term Paper Presentation ------------------------------- 15 %

Final Examination (comprehensive) ---------------------- 20 %

Class Structure

1. Lectures: Theory class

2. Laboratory: Some lectures will be conducted in Lab classes to get a hands-on experience with Matlab

3. Assignments: Few assignments based on Matlab

4. Projects: Project may consist several assignments related to each other

5. Paper Presentation: There will be at least one paper review session

5. Exams: There will be at least one final exam.