BMS415 Biomedical Signal Processing

5 ECTS - 3-0 Duration (T+A)- 7. Semester- 3 National Credit

Information

Code BMS415
Name Biomedical Signal Processing
Semester 7. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 5 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Doç. Dr. AHMET AYDIN


Course Goal

To teach digital signal processing methods used in biomedical engineering.

Course Content

Discrete time signals and systems. Discrete Fourier Trasnform. Sampling and reconstruction, quantization.Linear time invariant and discrete systems. Filter design methods:FIR,IIR. Fast Fourier Transform. Signal analysis using FFT. Optimal filtering. Processing of electrophysiological signals:ECG,EMG,EEG. Application of DFT, FFT, FIR and IIR filters for electrophysiological signals

Course Precondition

None

Resources

Sarp Ertürk, "Sayısal İşaret İşleme"

Notes

Lecture notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Can apply digital signal processing techniques and design systems
LO02 Can design digital filters
LO03 Can apply digital signal processing techniques on biological signals
LO04 Can analyze a digital system.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Scientific problems encountered in the field of medicine and medical technologies; the ability to solve problems by applying the technical approaches of mathematics, science and engineering sciences. 5
PLO02 Yetkinlikler - Öğrenme Yetkinliği To be able to improve oneself by embracing the importance of lifelong learning and by following the developments in science-technology and contemporary issues.
PLO03 Yetkinlikler - Öğrenme Yetkinliği Assess the contributions of engineering solutions on medicine, medical technologies and healthcare.
PLO04 Yetkinlikler - Öğrenme Yetkinliği Identifying problems related to biomedical engineering. 5
PLO05 Yetkinlikler - Öğrenme Yetkinliği Modeling problems related to biomedical engineering.
PLO06 Beceriler - Bilişsel, Uygulamalı Analyzing data and interpreting the results. 4
PLO07 Beceriler - Bilişsel, Uygulamalı To be able to use modern techniques and computational tools required for engineering applications. 5
PLO08 Beceriler - Bilişsel, Uygulamalı Ability to analyze and design a process in line with a defined goal. 5
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği To be able to understand the problems and wishes of the medical doctor in their scientific studies from an engineering point of view. 5
PLO10 Yetkinlikler - İletişim ve Sosyal Yetkinlik Expressing ideas verbally and in writing, clearly and concisely. 5
PLO11 Yetkinlikler - Alana Özgü Yetkinlik To be conscious of calibration and quality assurance systems in Biomedical Engineering.
PLO12 Beceriler - Bilişsel, Uygulamalı Design and Implement Experiments.
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Ability to act independently, set priorities and creativity.
PLO14 Yetkinlikler - İletişim ve Sosyal Yetkinlik Being aware of national and international contemporary issues in the field of Biomedical Engineering.
PLO15 Yetkinlikler - İletişim ve Sosyal Yetkinlik Ability to work in interdisciplinary teams.
PLO16 Yetkinlikler - Alana Özgü Yetkinlik To have a sense of professional and ethical responsibility.


Week Plan

Week Topic Preparation Methods
1 Introduction to Biomedical Signals and DSP Reading lecture materials Öğretim Yöntemleri:
Anlatım
2 Discrete time signals and systems. Reading lecture materials Öğretim Yöntemleri:
Anlatım
3 Linear time invariant and discrete systems. Reading lecture materials Öğretim Yöntemleri:
Anlatım
4 Block representationof discrete time systems. Reading lecture materials Öğretim Yöntemleri:
Anlatım
5 Sampling and reconstruction, quantization. Reading lecture materials Öğretim Yöntemleri:
Anlatım
6 Discrete Fourier Transform. DFT Reading lecture materials Öğretim Yöntemleri:
Anlatım
7 Fast Fourier Transform. FFT Reading lecture materials Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Mid-Term Exam Ölçme Yöntemleri:
Yazılı Sınav
9 Signal analysis using FFT. Reading lecture materials Öğretim Yöntemleri:
Anlatım
10 Filter design methods:FIR,IIR. Reading lecture materials Öğretim Yöntemleri:
Anlatım
11 Optimal filtering. Reading lecture materials Öğretim Yöntemleri:
Anlatım
12 Processing of electrophysiological signals-1:ECG,EMG . Reading lecture materials Öğretim Yöntemleri:
Anlatım
13 Processing of electrophysiological signals-2:EEG,EOG . Reading lecture materials Öğretim Yöntemleri:
Anlatım
14 Application of DSP for electrophysiological signals-1:DFT,FFT Reading lecture materials Öğretim Yöntemleri:
Anlatım
15 Review Reading lecture materials Öğretim Yöntemleri:
Anlatım
16 Term Exams Final Exams Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Final Exams 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 3 42
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 18 18
Total Workload (Hour) 114
Total Workload / 25 (h) 4,56
ECTS 5 ECTS