| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
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| ECTS | 10 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Learn Biosignals and their properties.
- Analysis biosignals with several signal processing algorithms used in engineering field and commenting on results.
- Learn new biosignal processing methods and develope new algorithms by using current techniques.
- Apply course units in homeworks on MATLAB or similar programs.
|
| Mode of Delivery | Face to face |
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| Prerequisites | No |
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| Recommended Optional Programme Components | None |
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| Course Description | This course introduces advanced techniques of biosignal analysis. Various estimation, detection and filtering methods are descibed and demonstrated on biomedical signals. The methods include harmonic analysis, autoregressive model, Wiener and Matched filters, linear discriminants, and independent components. All methods will be applied on biosignals such as ECG, EEG, EMG, PCG. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Biosignals and Properties.ECG, PCG, CP, EEG, EMG, ENG, ERP. Introduction to Biosignal Analysis. Objectives and difficulties of biosignal analysis, artefact types on signals nad properties of artefacts |
|
2nd Week |
Time Domain Filtering. Synchronized varaginf, moving average and derivative based filter types and applications |
|
3rd Week |
Frequency Domain Filtering. Rejecting artefacts with low frequency, high frequency and periodical waveshape. butterworth filters, wiener filter |
|
4th Week |
Event Detection. Detection of P,QRS, T waves from ECG signals, detection of heart sounds from PCG, detection of dicrotic notch from CP |
|
5th Week |
Event Detection. Detection of P,QRS, T waves from ECG signals, detection of heart sounds from PCG, detection of dicrotic notch from CP |
|
6th Week |
QRS Detection Methods. Derivative based methods, Pan-Tompkins algorithm |
|
7th Week |
Detection of EEG waves. Template matching method, coherence analysis, matching filter application |
|
8th Week |
Midterm Exam |
|
9th Week |
Disease Symptoms on Biosignals. Symptoms' wave properties and detecting, miocardial ischemia effects, ectopic beats |
|
10th Week |
Morphological Analysis of ECG.Correlation analysis. |
|
11th Week |
Activation Analysis in Biosignals. Root mean square, zero crossing rate, turn count, form factor calculations |
|
12th Week |
Frequency Domain Charecterization of Biosignals. Fourier spectrum, power spectral density (PSD), periodogram, windowing, PSD measurements |
|
13th Week |
Frequency Domain Charecterization of Biosignals. Fourier spectrum, power spectral density (PSD), periodogram, windowing, PSD measurements |
|
14th Week |
Classification methods. Supervised classification methods, unspervised classification methods |
|
| Recommended or Required Reading | (1)Biomedical Signal Analysis: A Case Study Approach by Rangaraj M. Rangayyan, Wiley Interscience, 2001.
(2)Biomedical Digital Signal Processing by Willis J. Tompkins. Prentice-Hall, 1993.
|
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| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
- Project
|
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| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
35 |
| Assignment |
1 |
10 |
| Project |
1 |
10 |
| Total(%) |
|
55 |
| Contribution of In-term Studies to Overall Grade(%) |
|
55 |
| Contribution of Final Examination to Overall Grade(%) |
|
45 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
72 |
72 |
| Preparation for Quiz |
0 |
0 |
0 |
| Individual or group work |
2 |
3 |
6 |
| Preparation for Final exam |
1 |
24 |
24 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
11 |
11 |
| Laboratory (including preparation) |
0 |
0 |
0 |
| Final exam |
1 |
96 |
96 |
| Homework |
1 |
12 |
12 |
| Project |
1 |
24 |
24 |
| Total Work Load | 287 |
| Total Work Load / 30 (h) | 9.56 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
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| Work Placement(s) | No |
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