School of Engineering \ Biomedical Engineering
Course Credit
ECTS Credit
Course Type
Instructional Language
Programs that can take the course
Department of Biomedical Engineering
BMM 412 course includes the basic concepts and techniques required for the analysis and processing of physiological signals. The course covers the analysis of ECG, EMG, EEG and respiratory signals in time and frequency domains, filter design, heart rate variability analysis and examination of evoked potentials.
Textbook and / or References
Biomedical Signal Processing: Principles and Techniques, DC Reddy, McGraw-Hill, 2005
The aim of the BMM 412 course is to teach students the basic concepts and techniques required for the analysis and processing of physiological signals and to provide practical skills in the development and application of signal processing algorithms. It is aimed that students can analyze and process various biomedical signals.
1. Ability to analyze physiological signals in time and frequency domains
2. Ability to design and implement digital filters
3. Ability to process ECG signals and analyze heart rate variability
4. Ability to understand the characteristics of EMG signals and apply processing techniques
5. Ability to analyze EEG signals and evaluate evoked potentials
6. Ability to process and analyze respiratory signals
7. Ability to develop signal processing algorithms in MATLAB/Python
8. Ability to use biomedical signal processing software effectively
Week 1: Fundamentals and Properties of Physiological Signals
Week 2: Time Domain Analysis
Week 3: Frequency Domain Analysis
Week 4: Digital Filter Design
Week 5: Processing of ECG Signals
Week 6: Heart Rate Variability Analysis
Week 7: Processing of EMG Signals
Week 8: Processing of EEG Signals
Week 9: Evoked Potentials
Week 10: Processing of Respiratory Signals
Week 11: Advanced Signal Processing Techniques
Week 12: Project Presentations
| Tentative Assesment Methods |
| Activities |
Number |
Weight (%) |
| Course Attendance/Participation |
1 |
5% |
| Laboratory |
- |
- |
| Application |
- |
- |
| Homework |
1 |
10% |
| Project |
- |
- |
| Presentation |
- |
- |
| Field Work |
- |
- |
| Internship |
- |
- |
| Course Boards |
- |
- |
| Quiz |
- |
- |
| Midterm Exam |
1 |
35% |
| Final Exam |
1 |
50% |
|
Total |
100% |
| Tentative ECTS-Workload Table |
| Activities |
Number/Weeks |
Duration (Hours) |
Workload |
| Course Hours (first 6 weeks) |
6 |
4 |
24 |
| Course Hours (last 6 weeks) |
6 |
4 |
24 |
| Laboratory |
- |
- |
- |
| Application |
- |
- |
- |
| Homework |
1 |
10 |
10 |
| Project |
- |
- |
- |
| Presentation |
- |
- |
- |
| Field Work |
- |
- |
- |
| Internship |
- |
- |
- |
| Course Boards |
- |
- |
- |
| Preparation for Quiz |
- |
- |
- |
| Preparation for Midterm Exam |
1 |
17 |
17 |
| Final Exam |
1 |
2 |
2 |
| Preparation for Final Exam |
1 |
20 |
20 |
| Study Hours Out of Class (preliminary work, reinforcement, etc.) |
12 |
6 |
72 |
| Total Workload | | |
169 |
| Total Workload / 30 | | |
169 / 30 |
| | |
|
| ECTS Credits of the Course | | |
6 |
|
Program Outcome
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Course Outcome
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A
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C, A
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A
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A, C
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A
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A, C
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A, C
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| 7 |
C, A
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A
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| 8 |
A, C
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A
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