Course Details

BIOMEDICAL SIGNAL PROCESSING

BENG422

Return to Classes
Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
5BENG422BIOMEDICAL SIGNAL PROCESSING3+0+035

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program BIOENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course This course introduces the principles of biomedical signal acquisition and processing using microprocessors and microcontrollers.
Course Content Signal analysis: time and frequency, sampling, digital signals, Fourier transform (FFT), power spectrum estimation, input windows, leakage, overlap, convolution and correlation properties, digital filters, physiological and mathematical models of bioelectricity: cell membrane, resting and action potentials, Nernst equation, volume conduction, prospective inverse problems, measurement of bioelectric signals: electrode properties, measurement systems, electrocardiography: origin of EKG, EKG-leads, ECG analysis, neurophysiology: nervous system, muscles, EEG, EP, EMG, ERG, EOG, signal analysis, electrostimulation: defibrillation, pacemakers, electrostimulation laboratory experiment: biosignal processing.
Course Methods and Techniques Lectures, practical assignments, projects using Python or MATLAB

Article review and case-based learning

Online quizzes and content via CANVAS
Prerequisites and co-requisities None
Course Coordinator Research Assist.Dr. Refika SULTAN DOĞAN https://avesis.agu.edu.tr/refikasultan.dogan refikasultan.dogan@agu.edu.tr
Name of Lecturers Research Assist.Dr. REFİKA SULTAN DOĞAN
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Books: Signals and Systems – Alan V. Oppenheim Digital Image Processing – Gonzalez & Woods
Bruce, Eugene N. Biomedical Signal Processing and Signal Modeling 978-1-60119-547-0, 978-0-471-34540-4 John Wiley & Sons 2001
Lecture materials will be shared weekly via the CANVAS platform. Instructor-prepared lecture slides, practical examples, academic articles, and supplemental videos will be provided.
-
-

Course Category
Mathematics and Basic Sciences %50
Engineering %30
Health %30
Field %60

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 25
Ödev 3 % 15
Proje/Çizim 1 % 30
Final examination 1 % 30
Total
6
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Tartışma 7 4 28
Yazılı Sınav 2 2 4
Grup Sunumu 1 2 2
Grup Projesi 1 2 2
Ev Ödevi 4 4 16
Proje 1 5 5
Rapor 1 3 3
Kişisel Çalışma 5 4 20
Takım/Grup Çalışması 5 5 25
Yüz Yüze Ders 14 3 42
Final Sınavı 1 3 3
Total Work Load   Number of ECTS Credits 5 150

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Define physiological and mathematical models in body
2 Vücuttaki biyoelektriğin matematiksel modellerini uygulayın
3 Choose appropriate domain to analyze the signal
4 Examine the types of bioelectric signals


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Signal Analysis
2 Introduction to signal analysis
3 Introduction to signal analysis
4 Introduction to signal analysis
5 Bioelectric signals examples (ECG, EMG, EOG)
6 Bioelectric signals examples (ECG, EMG, EOG)
7 Bioelectric signals examples (ECG, EMG, EOG)
8 Bioelectric signals examples (ECG, EMG, EOG)
9 Bioelectric signals examples (ECG, EMG, EOG)
10 Bioelectric signals examples (ECG, EMG, EOG)
11 Bioelectric signals examples (ECG, EMG, EOG)
12 Bioelectric signals examples (ECG, EMG, EOG)
13 Bioelectric signals examples (ECG, EMG, EOG)
14 Biosignal analysis


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 4 4 4 4 3 3 3 3 3 3 3 3
C2 3 3 3 3 4 4 4 4 4 4 4 4
C3 4 4 4 4 3 3 3 3 3 3 3 3
C4 4 4 4 4 4 4 4 4 4 4 4 4

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=72058&lang=en
Return to Classes