Physiological Signal Processing

Code:

L.BIO021

Acronym:

PSFI

Keywords
Classification	Keyword
OFICIAL	Biomedical Engineering

Instance: 2021/2022 - 1S

Active?	Yes
Web Page:	https://moodle.up.pt/course/view.php?id=3854
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	28	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 digital 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 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 objectives, therapy and rehabilitation, but also to foster research, specialization and innovation in these areas.

Working method

B-learning

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 using multimedia support, as well as the discussion of problems and specific cases of application. These classes incorporate a form of distributed evaluation that is based on verification questions aiming at testing the study of the course topics.

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, 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 practical classes also incorporate a distributed evaluation throughout the semester, in the form of online and/or in-person mini-tests, solving and group evaluating of problems in a "peer-to-peer" perspective, and a "study case" project to be developed during the last part of the semester.

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	40,00
Participação presencial	12,00
Trabalho laboratorial	48,00
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 mini-tests and verification questions, problem solving, the lab work, and the "study case" project planned for the semester. The distributed evaluation combines the grades of the individual mini-tests (25%), the lab work (groups of two students) at 25%, problem solving and evaluation in a “peer-to-peer” perspective (groups of 4 students) at 15%, and the study case project (groups of 4 students) at 25%. In addition, in certain TP classes several verification questions will be proposed that are weighted at 20% in the distributed evaluation. A minimum grade of 7/20 is mandatory for admission to the final exam.

Calculation formula of final grade

The final exam consists of a closed-book written examination whose duration is 90 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 evaluation (DE) and final exam (FE):

 

FG= 0.6×DE + 0.4×FE.

 

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

Observations

The Zoom link regarding each online lecture will be posted on the Moodle platform (look for the section pertaining to a particular week).