Fall 2018 Syllabus
Fairfield University School of Engineering
Course Number: CR331BEN331 
Course Name: BioEngineering DSP 
Course Time: Mon/Thur
12:30  1:45 PM 
Course Location: Bannow 333 
Schedule: 9/05/1812/11/18 
Final
Exam: Project 
Instructor: Jeffrey Denenberg 
Office: BNW 301C 
Office Phone: 2032544000x3330 
Hours: M/R 11:00 AMNoon, 
Email1: jeffrey.denenberg@ieee.org 
Goggle Voice: 2035139427 
Email2: jdenenberg@fairfield.edu 
This course
presents an overview of different methods used in biomedical signal processing.
Signals
with bioelectric
origin are given special attention and their properties and clinical
significance are
reviewed. In many
cases, the methods used for processing and analyzing biomedical signals are
derived from a
modeling perspective based on statistical signal descriptions. The purpose of
the
signal processing
methods ranges from reduction of noise and artifacts to extraction of
clinically
significant
features. The course gives each participant the opportunity to study the
performance of a
method on real,
biomedical signals.
Prerequisites: CS131 or CS141 or SW408, and MA126
or MA122, or permission of the instructor
Smith,
Steven W., The
Scientist and Engineer’s Guide to Digital Signal Processing, California
Technical Publishing, 1997, ISBN: 0966017633  Homework Problems
Java for
programmers, by D. Lyon, Java Digital Signal Processing by Lyon and Rao
Digital
Signal Processing, John G. Proakis, Dimitris K Manolakis, 4th
Edition, Pearson, 2006, ISBN: 9780131873742
Schaum’s Outline of Digital Signal Processing, Monson H. Hayes, McGrawHill 2012,
ISBN: 9760071635097
DSP Video Lectures, Rich Radke, Rensselaer Polytehnic Institute
1.
MatLab / Simulink
(download directly from mathworks following instructions posted on Blackboard).
2.
Java JDE and an
IDE (e.g. Eclipse)
3.
Recommended general
computer requirements – PC running Windows 10 or later, Adobe reader,
highspeed internet access, Internet Explorer or Firefox browser. You may encounter difficulties with the
lectures, simulation software, or internet testing software if you use Mac OS
or Linux. Please check all software
compatibilities for your system promptly.
No. 
Objective 
Outcomes 
1 
The students will
learn the principles of biomedical signal modeling. The student will become
proficient with the tools needed for simulating the models. 
Students will understand the fundamental concepts and
principles of Digital Signal Processing. 
2 
Students will use the Matlab and/or
Java to analyze and synthesize biomedical signals. 

3 
The Students will learn how
to analyze the biomedical signals 
Students analyze biomedical
signals. (2, Analysis) 
4 
Students synthesize
biomedical signals 

5 
Students will learn about
various biomedical devices and how they work. 
Students will research and report (Oral and written) on a
class of biomedical instruments. 
6 
Students will demonstrate the use and application of
MatLab software in the above application. (2, Application) 
*Objectives, ABET
Criteria outcomes (a, b,
c, k), and Bloom Cognitive
Level in parenthesis
Grade
allocation:
Mid
terms 
40%

Project 
40%

Homework 
20% 
Total 
100% 
The purpose of the exams is to convey your
understanding of the material; therefore, it is important that you show your
work. Even if you feel that the solution
to a problem is obvious; you must still explain why it is obvious. Furthermore; if you are asked to solve a
problem using a given technique; then please use that technique; otherwise, I
have no way to judge your understanding of the technique being tested.
Homework will be assigned from the book as your primary preparation for
the exams. We will review
select homework problems in class and you will be asked to work them on the
board for a participation grade. Homework must be
completed on time or it will not help with the exams. We will also incorporate design problems as
appropriate to the material. These
problems are designed to challenge you to think beyond what the book has told
you, and do real engineering. There may
be more than one correct answer.
If you understand how to do the homework problems you will have an
easier time with the exams.
Working with classmates to study, resolve problems, and learn the
material is expected and encouraged during normal course work. However, during individual evaluations (e.g.
quizzes, exams, individual projects, etc.) you are expected to comply with all
standards of academic honesty. You will
be graded fairly, and so your work should fairly represent your knowledge,
abilities, and effort, not that of others.
Any breach of integrity (including but not limited to: copying
solutions, internet solutions, copying from peers, claiming work or designs
without proper citation, etc.), will not only impact your ability to learn the
material and my ability to help you through proper feedback, it will result in
academic penalty. Any individual found in
breach of this code will fail the afflicted assignment and will be asked to
meet privately; any other offenses will be referred to the Dean for further
action, and could result in penalties as severe as expulsion from the
University.
If you have a documented disability and wish to discuss academic
accommodations, please contact: Academic and Disability Support Services (203)
2544000, x2615 and notify the course instructor within the first two weeks of
the semester.
TEACHER:
Distribute
syllabus.
Review
the material described in the syllabus.
Explain
material.
Identify
additional materials, Internet sites or books that clarify the material.
Relate
material to "real world" situations when possible.
Answer
questions.
Be
available to discuss problems.
Be receptive to new ideas.
Announce
business/class conflicts in advance.
Make
up missed classes.
Prepare
and administer exams and projects.
Grade
fairly.
Assign
appropriate homework problems.
STUDENT:
Be
familiar with the prerequisite material
Ask
questions.
Stay
current.
Study
the material described in the syllabus, preferably before it is covered in
class.
Complete
the assigned homework (all chapter problems with answers).
Obtain
class notes and homework if a class is missed.
Use
the library and the Internet to obtain supplemental material.
Prepare
for exams.
Ask
for help (tutors are available for assistance)
Follow
standards of academic integrity.
Class Topics and Order of Material
Wk 
Date 
Topic 
Text
Materials 
Homework 
Lecture Notes 
Outcome 
1 
9/06 
Course
Introduction: Why Digital? Projects! 
Review programming, 
Why Digital?Mitra 


2 
9/10 9/13 
Matlab 


Matlab Tutorial by
Dr Aliane


3 
9/17 9/20 
Fourier Series/Transform, Impulse Response, Convolution 
Ch5, 
Ch13: 1  3, 5, 6 Ch5: 1 – 4; 


4 
9/24 9/27 
Sampling: The analog world in
a computer Discrete Fourier Transform and FFT 


5 
10/01 10/04 
Laplace Transform,
zTransform Review for Exam 1 




6 
10/08 10/11 
Columbus Day –
No Classes Exam 1 – DSP
Basics (Thru 9/27) 




7 
10/15 10/18 
Exam 1 Reprise, Introduce Project Topics 



8 
10/22 10/25 
Discrete Convolution, Correlation Random Signals and Noise 
Ch6: 1  3, 5, 6; Ch7:
1  3, 5, 6 


9 
10/29 11/01 
Electrocardiograms Noise Reduction techniques 




10 
11/05 11/08 
Ultrasound imaging Tomography 




11 
11/12 11/15 
Project discussion 




12 
11/19 11/22 
Review for Exam 2 Thanksgiving – No Classes 




13 
11/26 11/29 
Exam 2 (10/111/08) Exam 2 Reprise 




14 
12/03 12/06 
Project Presentations 




15 
12/10 TBD 
Project Presentations 
Exam Week (12/13 – 12/19) 
Last day to submit materials 

