Graduate Course Proposal Form Submission Detail - EEL6282
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Approved by SCNS
Submission Type: New
Course Change Information (for course changes only):
Comments: Elective for Elect. Eng. To GC. Need makek-up policy. Confirm 2 LO? Emailed 3/11/16. Updated. GC approved; To USF Sys 4/21/16; to SCNS after 4/28/16. Desc too long. Corrected and resubmitted 6/15/16. Nmbr 6822 approved as 6282 eff 7/1/16
- Department and Contact Information
Tracking Number Date & Time Submitted 5224 2015-04-14 Department College Budget Account Number Electrical Engineering EN 2106000 Contact Person Phone Jessica Procko 46318 firstname.lastname@example.org
- Course Information
Prefix Number Full Title EEL 6282 Biomedical Systems and Pattern Recognition Is the course title variable? N Is a permit required for registration? N Are the credit hours variable? N Is this course repeatable? N If repeatable, how many times? 0 Credit Hours Section Type Grading Option 3 O - Other R - Regular Abbreviated Title (30 characters maximum) Biomed Systems & Pattern Recog Course Online? Percentage Online H - Face-to-face and blended (separate sections) 5
Covers 'models for analysis of biomedical systems, both theoretical and computer-based’ and ‘biomedical pattern spaces, feature extraction and statistical pattern recognition’ for insight into bio-systems and efficient integration with medical systems.
A. Please briefly explain why it is necessary and/or desirable to add this course.
Replacing Selected Topics with Permanent number; already listed in program
B. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service?
This course is a part of a two-course sequence for the Biomedical Systems graduate track in Electrical Engineering. Also, this course complements the College’s BME program.
C. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?
Yes, 3 or more times
D. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)
Ph.D. (doctoral degree) in EE.
- Other Course Information
To familiarize the students with the principles and techniques of biomedical systems and pattern recognition. Included are fluid flow, important electrical signals, measurements, models, responses, feature extraction, and pattern recognition. This can help medical researchers, medical instrument designers, and in the long run clinics.
B. Learning Outcomes
Upon successful completion of this course, the students will (1) demonstrate knowledge in the principles and techniques of biomedical systems and pattern recognition, and (2) be able to engage in the development and testing of medical devices.
C. Major Topics
Biomedical signals, images, and volumetric data; Basics of signals and systems: representation, analysis, and processing; biomedical examples and applications. Review of probability and statistics; random signals and multi-dimensional biomedical data. Biomedical pattern spaces, and feature extraction; statistical pattern recognition; biomedical applications. Examples are drawn from the lungs to the heart and from the brain to the limbs, and from fluid flow to electrical signal propagation in the heart and the brain.
Biomedical Signal Processing and Signal Modeling, E. N Bruce, Wiley Interscience,
2001. ISBN 0-471-34540-7.
Bi0omedical Instrumentation Technology and Applications, R. S. Khandpur, McGraw-
Hill, 2005, ISBN: 978-0-07-144784-3
But neither of them will be a required one.
E. Course Readings, Online Resources, and Other Purchases
The course is supplemented from other sources, and extensive material will be supplied to the students on USF’s ‘Canvas’.
F. Student Expectations/Requirements and Grading Policy
Typically, one Final Exam, 60%, and a mid-term exam or a term paper at the choice of the class, 40%.
G. Assignments, Exams and Tests
Homework problems, MATLAB assignments and example programs, a term paper at the option of the class, and exams as outlined in Section 11.
H. Attendance Policy
Course Attendance at First Class Meeting – Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation – Registration - 4.0101,
Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)
In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It’s the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.
I. Policy on Make-up Work
The make-up work policy will be announced in the syllabus issued before the start of the
semester in which it is offered. Typically, no make-up exams will be permissible. However,
make-up on homework and/or term-paper(s) may be allowed – with reasonable time
margins/limits, of course.
J. Program This Course Supports
Electrical Engineering MSEE/PhD
- Course Concurrence Information
BME (Biomedical Engineering).