| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
(1) This course will give a brief introduction on electronic circuit design for biopotential and physiological signals detection.
(2) This course also teaches students on various biomedical digital signal processing algorithm, like Fourier analysis, Fourier transform, digital filter design and discrete Fourier transform, short-time Fourier transform, wavelet transform and time-frequency analysis.
(3) This course also teaches students how to use artificial intelligence to judge biomedical signals. |
| 1.Possess professional knowledge in smart medical devices, smart manufacturing or smart management. |
| 2.Plan and implement research projects, and have the ability to solve problems independently. |
| 3.Ability to write scientific papers and communicate research results effectively. |
| 4.Integration in interdisciplinary research and innovative research skills. |
| 5.Possess insightful perspective on industry and globalization. |
| 6.Capability of leadership, management, planning, communication and lifelong learning. |
|
|
| Discussion |
| Other |
| Lecturing |
|
| Attendance |
| Oral Presentation |
| Assignment |
| Quiz |
| Other |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Course Introduction |
| Week 2 |
The Origin of Biopotentials |
| Week 3 |
Operational Amplifier (Op Amp) Circuits and Its Biomedical Applications |
| Week 4 |
Active Analog Filters |
| Week 5 |
Physiological Transducers |
| Week 6 |
Lab. Experiments: Op Amp Circuits, Active Analog Filters and Physiological Transducers |
| Week 7 |
Lab. Experiments: Op Amp Circuits, Active Analog Filters and Physiological Transducers |
| Week 8 |
Electrocardiogram (ECG) Measurement |
| Week 9 |
Mid-term Exam |
| Week 10 |
Lab. Experiment: ECG Measurement |
| Week 11 |
Lab. Experiment: ECG Measurement |
| Week 12 |
Group Project Presentation |
| Week 13 |
Measurement of Electromyogram (EMG), Electrooculogram (EOG) and Electroencephalogram (EEG) |
| Week 14 |
Measurement of Body Temperature and Breathing Rate |
| Week 15 |
Fourier analysis, Fourier transform, digital filter design and discrete Fourier transform, short-time Fourier transform, wavelet transform and time-frequency analysis |
| Week 16 |
Artificial intelligence on medicine |
| Week 17 |
Self-directed Learning (Video appreciation and discussion on topics related to Smart Medical Electronics) |
| Week 18 |
Self-directed Learning (Video appreciation and discussion on topics related to Smart Medical Electronics) |
|
| Evaluation |
Attendance 10%, Assignment 10%, Midterm exam 30%, Group Project Presentation 40%, Class participation 10%
|
| Textbook & other References |
1. Horowitz P and Hill W. The Art of Electronics, 2nd ed., Cambridge University Press, 1989
2. Dorf RC and Svoboda JA. Introduction to Electric Circuits, 5th ed., John Wiley & Sons, 2001
3. Webster JG. Medical Instrumentation: Application and Design, 3rd ed., John Wiley &Sons,1997
4. Enderle J, Bronzino J, Blanchard S. Introduction to Biomedical Engineering, ElsevierAcademic Press, 2005
5. Reddy DC. Biomedical Signal Processing: Principles and Technique, McGraw-HillPublishing Company Limited, 2005 |
| Teaching Aids & Teacher's Website |
| iLearning information exchange platform |
| Office Hours |
| Thursday: 12:00~13:00 |
| Sustainable Development Goals, SDGs |
| include experience courses：N |
|