| 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 |
| Quiz |
| Other |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Course Introduction |
| Week 2 |
Anatomy and Physiology |
| Week 3 |
Biopotentials |
| Week 4 |
Electrodes, Sensors and Transducers for Biomedical Signal Acquisition |
| Week 5 |
Amplifiers for Biomedical Signal Processing |
| Week 6 |
Filters for Biomedical Signal Processing |
| Week 7 |
Electrocardiography Circuit |
| Week 8 |
Circuits for Electromyography, Electrooculography, and Electroencephalography |
| Week 9 |
Circuits for Body Temperature and Breathing Rate Measurement |
| Week 10 |
Student Presentation |
| Week 11 |
Student Presentation |
| Week 12 |
Arduino |
| Week 13 |
APP Inventor 2 |
| Week 14 |
Introduction to Machine Learning |
| Week 15 |
Introduction to Deeping Learning |
| Week 16 |
Final Exam |
self-directed
learning |
02.Viewing multimedia materials related to industry and academia.
|
|
| Evaluation |
Attendance 20%
Student Presentation 40%
Final exam 40%
Class participation 5%
|
| 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(Link URL) |
| include experience courses：N |
|