ACADEMICS
Course Details
ELE694 - Biomedical Signal Processing
2024-2025 Fall term information
The course is not open this term
ELE694 - Biomedical Signal Processing
| Program | Theoretıcal hours | Practical hours | Local credit | ECTS credit |
| MS | 3 | 0 | 3 | 8 |
| Obligation | : | Elective |
| Prerequisite courses | : | - |
| Concurrent courses | : | - |
| Delivery modes | : | Face-to-Face |
| Learning and teaching strategies | : | Lecture, Question and Answer, Drill and Practice, Case Study, Problem Solving |
| Course objective | : | The course objective is to understand the basics of signal processing theory and utilizing some useful signal processing tools and methods efficiently for the signals frequently encountered in the fields of biology and medicine. |
| Learning outcomes | : | A student completing the course successfully will know the basics of signal processing theory to be used in biomedical studies, Learn the classification of biomedical signals and system modelling approaches, Have basic signal processing tools for the practical biomedical field problems, Efficiently use relevant computer programming tools for developing problem solutions, Learn possible use of artificial intelligence techniques in signal processing and biomedical applications, |
| Course content | : | 1. Introduction to biomedical signal processing 2. Classification of biomedical signals 3. Signals and measurements of biological systems: ECG,EEG,EMG 4. Memory and correlation analysis 5. Continuous and discrete models 6. Noise sources in biomedical systems 7. Noise cancellation and signal conditioning 8. Spectral analysis and modeling 9. Feature extraction, classification and artificial intelligence |
| References | : | Lecture Notes.; ; Bruce, E.N., Biomedical Signal Processing and Signal Modeling, John Wiley &; Sons, 2001.; ; Rangayyan, R. M., Biomedical Signal Analysis: A case-study approach, IEEE; Press/Wiley Inter-Science, 2002.; ; Oppenheim, A.V., Willsky, A.S., Signals and Systems, 2nd Edt, Prentice-Hall, 1997. |
| Weeks | Topics |
|---|---|
| 1 | Introduction to biomedical signal processing |
| 2 | Classification of biomedical signals |
| 3 | Signals and measurements of biological systems: ECG,EEG |
| 4 | Signals and measurements of biological systems: EMG, EOG |
| 5 | Memory and correlation analysis |
| 6 | Continuous time signals and models |
| 7 | Discrete time signals and models |
| 8 | Midterm Exam I |
| 9 | Noise sources in biomedical systems |
| 10 | Noise cancellation and signal conditioning |
| 11 | Spectral analysis and modeling |
| 12 | Midterm Exam II |
| 13 | Feature extraction, classification |
| 14 | Artificial intelligence in biomedical applications |
| 15 | Final exam |
| 16 | Final exam |
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 2 | 20 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Quiz | 0 | 0 |
| Midterms | 2 | 40 |
| Final exam | 1 | 40 |
| Total | 100 | |
| Percentage of semester activities contributing grade success | 60 | |
| Percentage of final exam contributing grade success | 40 | |
| Total | 100 | |
| Course activities | Number | Duration (hours) | Total workload |
|---|---|---|---|
| Course Duration | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, etc.) | 13 | 4 | 52 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework assignment | 2 | 20 | 40 |
| Quiz | 0 | 0 | 0 |
| Midterms (Study duration) | 2 | 20 | 40 |
| Final Exam (Study duration) | 1 | 30 | 30 |
| Total workload | 32 | 77 | 204 |
| Key learning outcomes | Contribution level | |||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1. | Has general and detailed knowledge in certain areas of Electrical and Electronics Engineering in addition to the required fundamental knowledge. | |||||
| 2. | Solves complex engineering problems which require high level of analysis and synthesis skills using theoretical and experimental knowledge in mathematics, sciences and Electrical and Electronics Engineering. | |||||
| 3. | Follows and interprets scientific literature and uses them efficiently for the solution of engineering problems. | |||||
| 4. | Designs and runs research projects, analyzes and interprets the results. | |||||
| 5. | Designs, plans, and manages high level research projects; leads multidiciplinary projects. | |||||
| 6. | Produces novel solutions for problems. | |||||
| 7. | Can analyze and interpret complex or missing data and use this skill in multidiciplinary projects. | |||||
| 8. | Follows technological developments, improves him/herself , easily adapts to new conditions. | |||||
| 9. | Is aware of ethical, social and environmental impacts of his/her work. | |||||
| 10. | Can present his/her ideas and works in written and oral form effectively; uses English effectively. | |||||
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest