Biomedical data acquisition and signal processing
| Title | Λήψη βιοϊατρικών δεδομένων και επεξεργασία σημάτων / Biomedical data acquisition and signal processing |
| Code | ΒΜ04 |
| Faculty | Engineering |
| School | Electrical and Computer Engineering |
| Cycle / Level | 1st / Undergraduate, 2nd / Postgraduate |
| Teaching Period | Winter |
| Coordinator | Dimitris Kugiumtzis |
| Common | Yes |
| Status | Active |
| Course ID | 600020746 |
Programme of Study: DPMS VIOÏATRIKĪ MĪCΗANIKĪ
Registered students: 26
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 1 | 1 | 5 |
| Academic Year | 2025 – 2026 |
| Class Period | Winter |
| Faculty Instructors |
|
| Instructors from Other Categories |
|
| Weekly Hours | 3 |
| Class ID | 600289850
|
Course Type 2021
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600289850
- eLearning: https://elearning.auth.gr/course/view.php?id=16132
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- English (Instruction, Examination)
Learning Outcomes
The scope of the course is to introduce the basic principles of digital signal processing and system modelling as practiced in biomedical research and clinical medicine.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work in teams
- Work in an interdisciplinary team
Course Content (Syllabus)
It covers methodologies and algorithms for the registration and visualization of biosignals, the use of filters and transforms (Fourier, wavelet, PCA), the coding of biomedical data, nonlinear analysis, feature extraction and biomedical systems modelling. It focuses on understanding the theoretical foundation of various biomedical signal processing techniques, as well as their practical advantages and limitations for the purpose of identifying the most promising approach according to the problem at hand. In addition, the implementation of selected signal processing algorithms will be demonstrated in specific tasks that concern real-life biosignals and biomedical systems. The course includes programming projects based on signals from e.g. cardiology, neurology and medical imaging.
Keywords
biosignal analysis, data acquisition, signal filters, noise, electroencephalogram, electrocardiogram
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Laboratory Teaching
Description
Different biomedical devices for biomedical data acquisition and software for signal processing.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | 1.6 | ✓ | ✓ | |
| Laboratory Work | 10 | 0.4 | ✓ | ✓ | |
| Reading Assigment | 25 | 1 | ✓ | ✓ | |
| Project | 40 | 1.6 | ✓ | ✓ | |
| Total | 114 | 4.6 |
Student Assessment
Description
50% of the final mark: written exam after each section in the form of quiz in elearning.
50% of the final mark: project on acquisition / processing of biosignals.
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Extended Answer Questions (Summative)
- Performance / Staging (Summative)
- Report (Summative)
- Labortatory Assignment (Summative)
Bibliography
Additional bibliography for study
1. Bruce, E. N. (2001). The Nature of Biomedical Signals. In: Biomedical Signal Processing and Modelling.
2. Kaniusas, Eugenijus. (2012). Fundamentals of Biosignals. In: Biomedical Signals and Sensors I: Linking physiological phenomena and biosignals.
3. Kaniusas, Eugenijus. (2012). Physiological and Functional Basis. In: Biomedical Signals and Sensors I: Linking physiological phenomena and biosignals.
4. Zouridakis, G. (2003). Biomedical Technology and Devices Handbook (1st ed.). CRC Press.
5. Song, G., Han, J., Zhao, Y., Wang, Z., & Du, H. (2017). A Review on Medical Image Registration as an Optimization Problem. Current medical imaging reviews, 13(3), 274–283.
6. Mambo, S. et al. (2018). 'A Review on Medical Image Registration Techniques'. World Academy of Science, Engineering and Technology, Open Science Index 133, International Journal of Computer and Information Engineering, 12(1), 48 - 55.
7. Biomedical Signal Analysis: A Case-Study Approach, Rangayyan, Wiley, 2015
8. Signals and Systems in Biomedical Engineering: Physiological Systems Modeling and Signal Processing, Devasahayam, Springer, 2019
Last Update
11-03-2024
