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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 signalsStudy the main mathematical tools of analysis and signal processingApplying signal processing to the study of biological signalsDevelop in the student the skills need to formulate the analysis of systemsUse appropriate softwareThe 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 processingII 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.

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Bioengineering
Last updated on: 2023-03-09

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