TÜRKÇE
ENGLISH
Information
| Code | EE652 |
| Name | Biomedical Signal Processing |
| Term | 2023-2024 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SAMİ ARICA |
| Course Instructor |
1 |
Course Goal / Objective
To introduce students to the signal processing techniques when applied specifically to biomedical signals: ECG, EEG and EMG. To teach methods for extracting Information from these signals and demonstrate practical implementations of signal processing techniques to biomedical signals.
Course Content
Biomedical signals and their origins: Electrocardiogram (ECG), Electroencephalography (EEG), Electromyogram (EMG). Basic signal processing methods: noise suppression, trend removal, power spectrum, partitioned into blocks/windows, time-frequency map, modelling, frequency estimation. ECG analysis: detection of R peaks and computation of heart-rate. EEG analysis: derivations/references, physiologic frequency bands and decomposition of these bands. EMG analysis: detection of bursts, power and frequency estimation, computation of envelope of an EMG signal.
Course Precondition
There are no prerequisites for the course.
Resources
There is no textbook that covers the topics of the course entirety. The course must be followed from the lecture and lecture notes.
Notes
No suggested additional course notes.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Integrate application-oriented signal processing techniquea for biomedical signal analysis. |
| LO02 | Discuss the selection of signal processing techniques for real biomedical signals. |
| LO03 | Evaluate ettects of different biomedical signal processing approaches using Matlab. |
| LO04 | Investigate Alternative Methods for Time and Frequency Domain Analysis of Biomedical Signals. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Being able to specialize in at least one of the branches that form the foundations of electrical-electronic engineering by increasing the level of knowledge beyond the undergraduate level. | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | To comprehend the integrity of all the subjects included in the field of specialization. | 5 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Knowing and following the current scientific literature in the field of specialization | 5 |
| PLO04 | Bilgi - Kuramsal, Olgusal | To be able to comprehend the interdisciplinary interaction of the field with other related branches. | 5 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to do theoretical and experimental work | 4 |
| PLO06 | Bilgi - Kuramsal, Olgusal | To create a complete scientific text by compiling the information obtained from the research. | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | To work on the thesis topic programmatically, following the logical integrity required by the subject within the framework determined by the advisor. | 4 |
| PLO08 | Bilgi - Kuramsal, Olgusal | To search for literature in scientific databases, particularly the ability to correctly and accurately scan databases and evaluate and categorize listed items. | 4 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Knowledge of English at a level that can easily read and understand a scientific text written in English in the field of specialization | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Compile information on his/her expertise in a presentation format and present it understandably and effectively. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Ability to write a computer program in a familiar programming language, generally for a specific purpose, specifically related to the field of expertise. | 4 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Being able to guide and take the initiative in environments that require solving problems related to the field | |
| PLO13 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Ability to communicate with people in an appropriate language | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | To be able to produce projects, policies, and processes in the field of expertise and to evaluate these elements | |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Ability to research new topics based on existing research experience | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction. Biomedical signals and their sources. Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG). | Textbook reading. | Öğretim Yöntemleri: Anlatım |
| 2 | Basic signal processing methods. Sampling and quantization. Digital signals. Linear time invariant systems. Filtering. Noise and trend removal. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım |
| 3 | Basic signal processing methods. Fourier transform. Power spectrum. Parametric modelling and power spectrum computation. Partitioning into blocks/windows. Short-time Fourier trasnsform. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım |
| 4 | Basic signal processing methods. Random signals. Probability distributions. Stationary and non-stationary signals. Specification of probability distribution. Expected value. Relation between correlation and power spectrum. Wigner-Ville distribution. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım |
| 5 | Basic signal processing methods. Signal space methods. Frequency estimation. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım |
| 6 | ECG Analysis. ECG electrodes and measurement. QRS complex. R-peak detection. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 7 | ECG Analysis. Tachogram. Obtaining Heart-rate variability. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | Textbook/course notes reading. | Öğretim Yöntemleri: Problem Çözme |
| 9 | EEG Analysis. Electrode placement. Derivations/references, physiologic frequency bands and decomposition of these bands. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 10 | EEG Analysis. EEG as a multichannel signal. Generating multi-input multi-output models. Computation of coherence. Connectivity between channels. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 11 | EEG Analysis. Phase synchronized signals: Evoked potentials. Detection and analysis of evoked potentials. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 12 | EMG analysis. Detection of bursts, power and frequency estimation, computation of envelope of an EMG signal. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 13 | Classification. Linear classifiers: Bayes and Fisher discriminant analysis. Support vector machines. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 14 | Feature extraction and selection. Feature specification and extraction of ECG, EEG the EMG signals. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 15 | Sample applications. Brain-computer interface. | Textbook reading/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 16 | Term Exams | Textbook/course notes reading. | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Textbook/course notes reading. | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 7 | 4 | 28 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 2 | 2 |
| Final Exam | 1 | 2 | 2 |
| Total Workload (Hour) | 144 | ||
| Total Workload / 25 (h) | 5,76 | ||
| ECTS | 6 ECTS | ||