Physiological Signal Processing

Code:

L.BIO021

Acronym:

PSFI

Keywords
Classification	Keyword
OFICIAL	Biomedical Engineering

Instance: 2023/2024 - 1S

Active?	Yes
Web Page:	https://moodle2324.up.pt/course/view.php?id=5891
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Bachelor in Bioengineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.BIO	44	Syllabus	3	-	6	26	52

Teaching language

Portuguese and english

Objectives

The objective of this course unit is to motivate students to the nature and diversity of physiological signals (e.g. EMG, EEG, ECG), to familiarize students with the theory foundations in the area of discrete-time signal processing, and to convert this knowledge into practical skills allowing students to understand and design important processes in physiological signal processing, including acquisition, conditioning, filtering, analysis and extraction and representation of relevant information. 

Learning outcomes and competences

Upon successful conclusion of this curricular unit, students will be able to use techniques and technologies of physiological signal processing, by strengthening not only their application to diagnosis, therapy and rehabilitation objectives, but also to foster research, specialization and innovation in these areas.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Pre-requisites: basic knowledge in signal theory, notably discrete-time signals and systems, and Fourier analysis.

Program

1. Introduction to electrophysiology
2. Discrete-time signals and systems
3. Sampling and reconstruction of signals
4. The Z transform
5. The discrete Fourier transform (DFT)
6. Discrete-time filters
7. The auto-correlation and cross-correlation
8. Introduction to spectral estimation
9. Physiological signal processing study cases

 

Mandatory literature

Oppenheim, Alan V.; Discrete-Time Signal Processing. ISBN: 0-13-216771-9

Complementary Bibliography

Bronzino, Joseph Daniel, 1937- 340; The biomedical engineering handbook
Enderle, Joseph Bronzino John; Introduction to Biomedical Engineering. ISBN: 0-12-238662-0
Bruce, Eugene N.; Biomedical signal processing and signal modeling. ISBN: 0-471-34540-7

Teaching methods and learning activities

The teaching methodology is based on lectures and laboratory classes. The former include the presentation and illustration of theoretical contents of the course in complement to videos that will be made available with explanations of the theory underlying several course topics, as well as the discussion of problems and specific cases of application.

The laboratory classes involve conventional or Matlab-based solving of problems that are proposed to consolidate and reinforce the applied perspective of the main topics of the course, especially in a "peer-to-peer teaching-assessment perspective", as well as experimental work using Matlab, the Biopac platform for the acquisition and analysis of physiological signals, and/or a real-time digital signal processing platform.

The laboratory classes also incorporate a form of distributed assessment throughout the semester, as a result of i) problem-solving by students and group evaluation in a "peer-to-peer" (P2P) perspective, and ii) of the realization of laboratory work involving physiological signals, among others, which is assessed by the instructor.

An extra-class form of distributed assessment also exists that is supported by the Moodle platform and that is based on verification questions aiming at testing the study by students of the essential course topics.

Software

Matlab 6 R12.1

keywords

Technological sciences > Technology > Computer technology > Signal processing

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	45,00
Participação presencial	13,75
Trabalho laboratorial	41,25
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	70,00
Frequência das aulas	52,00
Trabalho de campo	14,00
Trabalho laboratorial	26,00
Total:	162,00

Eligibility for exams

In order to be admitted to the final exam, students should comply with the FEUP General Evaluation Rules concerning the allowed maximum number of missed classes, and should perform the individual verification questions (VQ), P2P problem solving, and the lab projects to be developed during the semester.

The distributed assessment combines the scores of the lab work (groups of four students) at 50%, and individual problem-solving and group evaluation in a “peer-to-peer” perspective, at 25%. In addition, quizzes containing several verification questions will be proposed via Moodle, and in an extra-class modality, that are weighted at 25% in the distributed assessment. A minimum score of 7/20 is mandatory in the distributed assessment component for admission to the final exam.

Calculation formula of final grade

The final exam consists of a closed-book written examination whose duration is 120 minutes. Students will be provided with a formulae sheet.

The final grade (FG) is obtained using the following formula which combines the grades of two components: distributed assessment (AD) and final exam (FE):

 

FG= 0.55×AD + 0.45×FE.

 

The scale for both components is [0, 20]. A minimum classification of 7/20 is required for either one of the two components.