Biosignals Processing and Analysis

Recommended Prerequisites

Mathematical Analysis (I, II, III), Linear Algebra and Analytical Geometry , Computers and Programming.

Teaching Methods

Theoretical classes with detailed presentation, using audio-visual means, of the concepts, principles and fundamental theories. Theoretical-practical classes for solving practical exercises, which require the combination of different theoretical concepts in order to promote critical reasoning in the presence of more complex problems.
Laboratory classes to solve practical exercises and small application projects using the Matlab tools for signal processing whose objective is to demonstrate the practical usefulness of the theory taught in T and TP classes.

Learning Outcomes

Acquire knowledge on signal analysis and processing techniques using linear time-invariant systems, with emphasis in applications with biosignals used in biomedical instrumentation.

Work Placement(s)

No

Syllabus

1. Introduction to signals and systems.
2. Fourier representation of signals and linear time-invariant systems.
3. The Laplace transform.
4. The Z transform.
5. Introduction to digital filtering and control theory.

Head Lecturer(s)

Marco Alexandre Cravo Gomes

Assessment Methods

Assessment
Laboratory work or Field work: 30.0%
Frequency: 35.0%
Exam: 35.0%

Bibliography

Simon Haykin and Barry Van Veen, Signals and Systems, 2nd Edition, 2003 John Wiley & Sons. Inc, ISBN 0-471-16474-7

Alex Palamides and Anastasia Veloni, Signals and Systems Laboratory with Matlab, 2011 CRC Press, ISBN 978-1-4398-3055-0

LEITURA COMPLEMENTAR

A. Oppenheim, A. Willsky and S. Hamid, Signals and Systems, 2nd Edition, 1996 Pearson Publisher, ISBN-13: 978-0138147570

Rangaraj M. Rangayyan, Biomedical Signal Analysis, 2nd Edition, 2015 IEEE Press, ISBN-13: 978-0470911396

Abdulhamit Subasi, Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach, 2019 Academic Press, ISBN-13: 978-0128174449.