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Signal Processing and Analysis

Code 9101
Year 2
Semester S2
ECTS Credits 6
Workload PL(30H)/T(30H)
Scientific area Bioengenharia
Entry requirements No entry requirement applies
Mode of delivery Presential
Work placements Not applicable
Learning outcomes Introduce to the study of processing and analysis signals
Study the main mathematical tools of analysis and signal processing
Applying signal processing to the study of biological signals
Develop in the student the skills need to formulate the analysis of systems
Use appropriate software
The student should be able to:
- Formulate problems using the studied tools
- Process signals acquired and stored on a computer
- Understand the differences between discrete and continuous domains and their properties
- Analyse the frequency response of a systems
- Obtain the response of a system to any input based on the impulse response
- Modeling signals using the tools studied
- Understand the influence of noise on a signal
- Extract the information contained in a signal in order to highlight the characteristics of the system that produces it
- Develop theoretical models that describe the operation of biomedical systems
Syllabus I The nature of biomedical signals - The reasons for studying biomedical signal processing
II Memory and correlation: Properties of operators and transformations; Concepts of memory, energy, power and autocorrelation.
III Impulse response: Example “glucose control“; Convolution form of an LTI system; Convolution for continuous-time systems; Relation of impulse response to differential equation.
IV Frequency Response: Example “Transducers for measuring knee angle“; Sinusoidal inputs to continuos-time and discrete-time LTI systems; Frequency response of nonlinear systems.
V Modeling continuous-time signals as sums of sine waves: Introductory example – Example “Analysis of circadian rhythm"; Sinusoidal basis functions; The Fourier series; Parseval's relation for periodic signals; The Fourier Transform and their properties;
VI Responses of linear continuous-time filters to arbitrary inputs: Introductory example; Direct and inverse LaPlace Transform; Properties of LaPlace Transforms.
Main Bibliography Biomedical Signal Processing and Signal Modeling, Eugene N. Bruce, Wiley ,December 2000 (ISBN: 978-0-471-34540-4).

Biomedical Signal Analysis: A Case-Study Approach by Rangaraj M. Rangayyan, Wiley-IEEE Press, January 2002 (ISBN: 978-0-471-20811-2).

Biomedical Signal Processing Principles and Techniques, D. C. Reddy, McGraw-Hill, May 2005 (ISBN: 0071247742).

Biosignal Processing: Foundations for Biomedical Engineers, Parker S. Ruth and Christopher M. Neils, Oct 11, 2020 (979-8688184860).
Teaching Methodologies and Assessment Criteria Throughout the semester are held 10 quizzes (MiniTestes), one written test, and a written report.

Final classification = 0.25*MiniTestes + 0.25*Freq F1 + 0.25*Freq F2+ 0.25*report

Final exam classification = 0.25*MiniTestes + 0.5*writen_test + 0.25*report
Language Portuguese. Tutorial support is available in English.
Last updated on: 2023-03-09

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