The aim of this course is informing students about biological signal processing methods and give them the opportunity to use their engineering skills in this field.
Course Content
This course contains; Introduction to Biological Signals ,Filtering for Removal of Artifacts (Noise, Basics of Filtering),Filtering for Removal of Artifacts (Time-domain filters),Filtering for Removal of Artifacts (Frequency-domain filters),Detection of Events ,Waveshape and Waveform Complexity ,Frequency-domain Characterization ,Modelling Biomedical Systems ,Analysis of Nonstationary and Multicomponent Signals ,Pattern Classification - Part 1,Pattern Classification - Part 2,Pattern Classification - Part 3,Student Presentations,Student Presentations.
Course Learning Outcomes
Teaching Methods
Assessment Methods
A Student who successfully complete the course
1- Gains a general knowledge about biological signal processing.
2 -learns the required methods to remove artifacts from the signal.
3- learns how to analyze the signal in frequency domain.
4- Learns stationary and nonstationary signal analyses.
5- Learns pattern classification and decision makine for diagnosis.
6- Has the capability to review and present the research articles in the field.
Teaching Methods:
Assessment Methods:
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Biological Signals
2
Filtering for Removal of Artifacts (Noise, Basics of Filtering)
3
Filtering for Removal of Artifacts (Time-domain filters)
4
Filtering for Removal of Artifacts (Frequency-domain filters)
5
Detection of Events
6
Waveshape and Waveform Complexity
7
Frequency-domain Characterization
8
Modelling Biomedical Systems
9
Analysis of Nonstationary and Multicomponent Signals
10
Pattern Classification - Part 1
11
Pattern Classification - Part 2
12
Pattern Classification - Part 3
13
Student Presentations
14
Student Presentations
Resources
R.M. Rangayyan. Biomedical Signal Analysis, 2nd Edition.
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
50
Rate of Final Exam to Success
50
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
14
3
42
Guided Problem Solving
0
0
0
Resolution of Homework Problems and Submission as a Report
2
25
50
Term Project
0
0
0
Presentation of Project / Seminar
1
50
50
Quiz
0
0
0
Midterm Exam
1
35
35
General Exam
1
55
55
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
232
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(232/30)
8
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.
Detail Informations of the Course
Course Description
Course
Code
Semester
T+P (Hour)
Credit
ECTS
BIOLOGICAL SIGNAL PROCESSING
BEBY1115696
Fall Semester
3+0
3
8
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of Course
English
Course Level
Second Cycle (Master's Degree)
Course Type
Elective
Course Coordinator
Assist.Prof. Zafer İŞCAN
Name of Lecturer(s)
Assist.Prof. Zafer İŞCAN
Assistant(s)
Aim
The aim of this course is informing students about biological signal processing methods and give them the opportunity to use their engineering skills in this field.
Course Content
This course contains; Introduction to Biological Signals ,Filtering for Removal of Artifacts (Noise, Basics of Filtering),Filtering for Removal of Artifacts (Time-domain filters),Filtering for Removal of Artifacts (Frequency-domain filters),Detection of Events ,Waveshape and Waveform Complexity ,Frequency-domain Characterization ,Modelling Biomedical Systems ,Analysis of Nonstationary and Multicomponent Signals ,Pattern Classification - Part 1,Pattern Classification - Part 2,Pattern Classification - Part 3,Student Presentations,Student Presentations.
Course Learning Outcomes
Teaching Methods
Assessment Methods
A Student who successfully complete the course
1- Gains a general knowledge about biological signal processing.
2 -learns the required methods to remove artifacts from the signal.
3- learns how to analyze the signal in frequency domain.
4- Learns stationary and nonstationary signal analyses.
5- Learns pattern classification and decision makine for diagnosis.
6- Has the capability to review and present the research articles in the field.
Teaching Methods:
Assessment Methods:
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Biological Signals
2
Filtering for Removal of Artifacts (Noise, Basics of Filtering)
3
Filtering for Removal of Artifacts (Time-domain filters)
4
Filtering for Removal of Artifacts (Frequency-domain filters)
5
Detection of Events
6
Waveshape and Waveform Complexity
7
Frequency-domain Characterization
8
Modelling Biomedical Systems
9
Analysis of Nonstationary and Multicomponent Signals
10
Pattern Classification - Part 1
11
Pattern Classification - Part 2
12
Pattern Classification - Part 3
13
Student Presentations
14
Student Presentations
Resources
R.M. Rangayyan. Biomedical Signal Analysis, 2nd Edition.
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
