TÜRKÇE
ENGLISH
Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| ELECTRICAL-ELECTRONICS ENGINEERING (MASTER) (WITH THESIS) (ENGLISH) | |
| Code | EE652 |
| Name | Biomedical Signal Processing |
| Term | 2018-2019 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 |
The current term course schedule has not been prepared yet.
|
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
Resources
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. |
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. | |
| 2 | Basic signal processing methods. Sampling and quantization. Digital signals. Linear time invariant systems. Filtering. Noise and trend removal. | Textbook reading/Computer application. | |
| 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. | |
| 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. | |
| 5 | Basic signal processing methods. Signal space methods. Frequency estimation. | Textbook reading/Computer application. | |
| 6 | ECG Analysis. ECG electrodes and measurement. QRS complex. R-peak detection. | Textbook reading/Computer application. | |
| 7 | ECG Analysis. Tachogram. Obtaining Heart-rate variability. | Textbook reading/Computer application. | |
| 8 | Mid-Term Exam | Textbook/course notes reading. | |
| 9 | EEG Analysis. Electrode placement. Derivations/references, physiologic frequency bands and decomposition of these bands. | Textbook reading/Computer application. | |
| 10 | EEG Analysis. EEG as a multichannel signal. Generating multi-input multi-output models. Computation of coherence. Connectivity between channels. | Textbook reading/Computer application. | |
| 11 | EEG Analysis. Phase synchronized signals: Evoked potentials. Detection and analysis of evoked potentials. | Textbook reading/Computer application. | |
| 12 | EMG analysis. Detection of bursts, power and frequency estimation, computation of envelope of an EMG signal. | Textbook reading/Computer application. | |
| 13 | Classification. Linear classifiers: Bayes and Fisher discriminant analysis. Support vector machines. | Textbook reading/Computer application. | |
| 14 | Feature extraction and selection. Feature specification and extraction of ECG, EEG the EMG signals. | Textbook reading/Computer application. | |
| 15 | Sample applications. Brain-computer interface. | Textbook reading/Computer application. | |
| 16 | Term Exams | Textbook/course notes reading. | |
| 17 | Term Exams | Textbook/course notes reading. |
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 | ||