Information Package / Course Catalogue
Biomedical Signal Processing and Machine Learning
Course Code: CSE435
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: English
Work Placement: N/A
Theory: 2
Prt.: 2
Credit: 3
Lab: 0
ECTS: 6
Objectives of the Course

The aim of this course is to introduce the concepts of biomedical systems, signal processing and biomedical machine learning and to have students apply them. At the end of the course, the student will recognize biomedical devices such as EMG, ECG, EEG, Phonocardiogram, analyze the signals from these devices and learn about applying machine learning to these signals.

Course Content

Basic concepts, Biomedical device types, Biomedical signals, Biomedical signal processing techniques, Feature extraction and dimensional reduction, Biomedical signal classification applications.

Name of Lecturer(s)
Learning Outcomes
1.Recognizing biomedical devices such as EEG, EMG, ECG, Phonocardiogram
2.Ability to collect and process biomedical signals
3.Signal filtering
4.To be able to extract features in time and frequency domains
5.To be able to biomedical signal classification
Recommended or Required Reading
1.Subasi, A. (2019). Practical guide for biomedical signals analysis using machine learning techniques: A MATLAB based approach. Academic Press.
2.Naik, G. (2020). Biomedical Signal Processing. Springer Singapore.
Weekly Detailed Course Contents
Week 1 - Theoretical & Practice
Biomedical Devices and Basic Concepts
Week 2 - Theoretical & Practice
Biomedical Signals-EMG-ECG
Week 3 - Theoretical & Practice
Biomedical Signals-Phonocardiogram
Week 4 - Theoretical & Practice
Biomedical Signals-EEG
Week 5 - Theoretical & Practice
Biomedical Signals-Other Signals
Week 6 - Theoretical & Practice
Biomedical Signal Processing- Time Domain
Week 7 - Theoretical & Practice
Biomedical Signal Processing- Frequency Domain
Week 8 - Theoretical & Practice
Biomedical Signal Processing- Time-Frequency Domain
Week 9 - Theoretical & Practice
Biomedical Signal Processing- Time-Frequency Domain
Week 10 - Theoretical & Practice
Biomedical Signal Processing- Noise and Filtering
Week 11 - Theoretical & Practice
Feature Extraction Methods
Week 12 - Theoretical & Practice
Feature Reduction and Selection Methods
Week 13 - Theoretical & Practice
Biomedical Signal Classification
Week 14 - Theoretical & Practice
Biomedical Signal Classification Applications
Assessment Methods and Criteria
Type of AssessmentCountPercent
Term Assignment1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140228
Assignment140114
Term Project116824
Midterm Examination116824
Final Examination1161632
TOTAL WORKLOAD (hours)150
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
OÇ-1
4
4
5
5
4
OÇ-2
2
3
3
5
5
OÇ-3
5
5
4
5
4
OÇ-4
4
4
4
4
5
OÇ-5
3
2
3
3
4
Adnan Menderes University - Information Package / Course Catalogue
2026