INTERNATIONAL BURCH UNIVERSITY
Faculty of Engineering and Natural Sciences
Department of Genetics and Bioengineering
2016-2017

SYLLABUS
Code Name Level Year Semester
GBE 325 Biomedical Signals and Systems Undergraduate 3 Fall
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
Area Elective 5 2 + 2 125 English

Instructor Assistant Coordinator
Almir Badnjević, Assist. Prof. Dr. Assist. prof. Almir Badnjević Almir Badnjević, Assist. Prof. Dr.
[email protected] [email protected] no email

This course will introduce students to medical and biomedical engineering concepts. The focuses are on how signal analysis can clarify the understanding of biomedical signal interpretation and diagnosis. Topics include EEGs, ECGs, EMGs, respiratory and blood pressure (how they are generated and measured), biosignals as random processes, spectral analysis, wavelets, time-frequency functions, and signal processing for pattern recognition.

COURSE OBJECTIVE
The cognitive, affective and behavioral objectives of this course are following:

• Introduction to the principles of biomedical signals and systems through ECG, EEG, EMG, NIBP, IBP and respiratory examples.
• Explaining the importance of engineering in medicine.
• Giving an outline of characteristics of biomedical signals.
• Providing basic concepts about the human heart.
• Providing basic concepts about the respiratory system

COURSE CONTENT
Week
Topic
  1. Summary and history of biomedical engineering
  2. Cell physiology, bio-potentials, membrane, and active potentials
  3. Bioelectrical phenomena, neurons, synaptic transmission
  4. Biomedical signals: ECG, EEG, EMG, EOG, respiratory signal, biomedical sensors, biomedical signals processing
  5. Human heart, cardio-cycle, electrocardiogram, vectocardiogram, electrical field of the heart, methods of ECG signal acquisition
  6. Methods for acquisition, processing and visualization of ECG signal, heart’s rhythm diagnostic
  7. ECG waveform and significant segments, ECG interpretation and diagnostics, pacemaker
  8. MID-TERM EXAM WEEK
  9. Respiratory signal, measurement, extraction from ECG, and measuring respiratory signals
  10. Blood pressure, invasive and non-invasive measurement methods, biosensors and transducers
  11. Methods for acquisition, processing and visualization of EEG signal
  12. Recording and interpretation of EEG, basic concepts and EEG phenomena
  13. Electrodes for bio-potential measurement, basic electrochemical processes in the cell and tissues, aspects and methods of bioimpedance measurement
  14. Electrochemical sensors and dialysis: Chemical sensors, separation of the blood components
  15. FINAL EXAM WEEK

LABORATORY/PRACTICE PLAN
Week
Topic

    TEACHING/ASSESSMENT
    Description
    • Interactive Lectures
    • Discussions and group work
    Description (%)
    Method Quantity Percentage (%)
    Homework120
    Midterm Exam(s)120
    Laboratory120
    Total: 60
    Learning outcomes
    • knowledge of biomedical system modelling
    • different aspects and methods of applying engineering principles in medicine
    • characteristics of biomedical signals
    • principles of design and implementation of medical devices for physiological signal processing
    TEXTBOOK(S)
    • Raden, J.F. (2010). Handbook of Modern Sensors, Physics, Designs and Applications. New York, NY, USA: Springer-Verlag

    ECTS (Allocated based on student) WORKLOAD
    Activities Quantity Duration (Hour) Total Work Load
    Lecture (14 weeks x Lecture hours per week)15230
    Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)15230
    Midterm Examination (1 week)122
    Final Examination(1 week)122
    Preparation for Midterm Examination11414
    Preparation for Final Examination11515
    Assignment / Homework/ Project11414
    Seminar / Presentation11818
    Total Workload: 125
    ECTS Credit (Total workload/25): 5