Biomedical signal processing
| Title | Επεξεργασία ιατρικών σημάτων / Biomedical signal processing |
| Code | ΙΠΒ004 |
| Interdepartmental Programme | IPPS "Medical Informatics" (2019-today) |
| Collaborating Schools | Medicine Informatics Electrical and Computer Engineering |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Spring |
| Coordinator | Anthony Aletras |
| Common | No |
| Status | Active |
| Course ID | 600004408 |
Programme of Study: IPPS "Medical Informatics" (2019-today)
Registered students: 0
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 2 | 1 | 7.5 |
| Academic Year | 2017 – 2018 |
| Class Period | Spring |
| Faculty Instructors |
|
| Instructors from Other Categories |
|
| Weekly Hours | 2 |
| Class ID | 600111940
|
Course Type 2016-2020
- Background
Course Type 2011-2015
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600111940
- At the Website of the School: http://promesip.med.auth.gr/
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Good math basis.
Learning Outcomes
They understand the nature of the biomedical signals and the basic principles of the signal processing, so to apply them in recording and analysing the biomedical signals for diagnostic purposes.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
- Generate new research ideas
- Be critical and self-critical
Course Content (Syllabus)
The course aims to present biomedical signal processing issues. Alongside the individual specificities of these fields, presented techniques of computer science applied on biomedical signals aims to familiarize students with practical issues related signals, such as ECG and EEG.
This course includes:
1. Basic signal processing elements (Fourier analysis, filters, convolution, ...)
2. Noise reduction
3. Applications in biomedical signals.
4. Big data analysis
Keywords
signal processing, biomedical engineering, digital analysis, filteres, transforms
Educational Material Types
- Notes
- Slide presentations
- Multimedia
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 90 | 3 | ✓ | ||
| Laboratory Work | 12 | 0.4 | ✓ | ||
| Fieldwork | 4 | 0.1 | ✓ | ||
| Reading Assigment | 20 | 0.7 | ✓ | ||
| Tutorial | 4 | 0.1 | ✓ | ||
| Field trips and participation in conferences / seminars / activities | 10 | 0.3 | ✓ | ||
| Project | 75 | 2.5 | ✓ | ||
| Written assigments | 10 | 0.3 | ✓ | ✓ | |
| Total | 225 | 7.5 |
Student Assessment
Description
The evaluation is based on both bibliographic or field work, or on the basis of attending seminars / conferences, as well as on the basis of the preparation of a specific project at the end of the course. In the presentation of the latter, there exists an evaluation of presentation skills and development of methodological solutions proposed by the students.
Student Assessment methods
- Performance / Staging (Summative)
- Report (Formative)
- Labortatory Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Ψηφιακή επεξεργασία σημάτων
Συγγραφέας: Σταύρος Μ. Πανάς
Εκδότης: University Studio Press
ISBN: 9789601201757
Additional bibliography for study
Digital Signal Processing (4th Edition)(2006)
John G. Proakis, Dimitris K Manolakis
Published by Prentice Hall.
ISBN-13: 978-0131873742
ISBN-10: 0131873741
Last Update
10-05-2017
