Course Information
Course title
 Biomedical Signal Investigation 
Semester
 111-1 
Designated for
 COMMON GENERAL EDUCATION CENTER  Master’s Program in Smart Medicine and Health Informatics  
Instructor
 WEN-CHAU WU 
Curriculum Number
 MHI7010 
Curriculum Identity Number
 H45EM7010 
Class
  
Credits
 3.0 
Full/Half
Yr.
 Half 
Required/
Elective
 Elective 
Time
 Monday 6,7,8(13:20~16:20) 
Remarks
 Restriction: MA students and beyond AND Restriction: within this department (including students taking minor and dual degree program)
The upper limit of the number of students: 20. 
  
Course introduction video
 
Table of Core Capabilities and Curriculum Planning
 Association has not been established
Course Syllabus
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Course Description

1. This is a compulsory course for Smart MHI students.
2. This course is designed for students to learn the following aspects of biomedical signals: properties, acquisition, processing methods, and clinical/preclinical applications.  

Course Objective
 By the end of this course, the students are expected to
1. have an advanced understanding of the principles of biomedical signal processing;
2. have the ability to perform practical signal processing;
3. have the ability to understand the descriptions of biomedical signal acquisition and processing in literature. 
Course Requirement
 Prerequisite courses are college calculus and college physics (at least two credits for each). 
Student Workload (expected study time outside of class per week)
  
Office Hours
 Note: Fridays, 10:00 a.m. – 12:00 noon (appointment required) 
Designated reading
 To be announced in class. 
References
 1. Alan V. Oppenheim, Alan S. Willsky, with S. Hamid Nawab. Signals and Systems. 2nd edition. Upper Saddle River: Prentice-Hall, 1996.
2. Advanced methods of biomedical signal processing. Edited by Sergio Cerutti and Carlo Marchesi. Wiley; Piscataway, NJ; IEEE Press 2011. 
Grading
  
No.
Item
%
Explanations for the conditions
1. 
 Midterm exam 
25% 
 Closed-book written exam 
2. 
 Final exam 
25% 
 Closed-book written exam 
3. 
 Term project 
20% 
  
4. 
 Homework 
20% 
  
5. 
 In-class engagement 
10% 
  
 
Progress
Week
Date
Topic
Week 1
 9/05  1. Course overview
2. Introduction to biomedical signals 
Week 2
 9/12  Time-domain analysis 
Week 3
 9/19  Fourier analysis 
Week 4
 9/26  Filtering 
Week 5
 10/03  Principal component analysis 
Week 6
 10/10  No class 
Week 7
 10/17  Independent component analysis
 
Week 8
 10/24  Midterm exam 
Week 9
 10/31  Panel discussion: homework and term project 
Week 10
 11/07  Panel discussion: homework and term project 
Week 11
 11/14  Time-frequency analysis 
Week 12
 11/21  Time-frequency analysis 
Week 13
 11/28  Lab tour 
Week 14
 12/05  Final presentation 
Week 15
 12/12  Final presentation 
Week 16
 12/19  Final exam