EEL-6075                              BIOSIGNAL PROCESSING I                                 FALL 2005

Dr. Armando Barreto                             EC - 3956                                       barretoa@fiu.edu

(305)348-3711                                                                                       (305) 348-3707   Fax

 

Class Meetings: Tuesday and Thursday 4:10 PM – 5:25 PM

 

Office hours: Tuesday and Thursday: 2:00 PM – 3:00 PM

 

Objective:

 

To familiarize the student with the generation, measurement and digital signal processing of some of the most relevant signals of biomedical origin. The course will focus mainly on the Electroencephalogram (EEG), the Electrocardiogram (ECG) and the Electromyogram (EMG), but the measurement principles and signal processing techniques covered are of a general nature.

 

Prerequisites:

 

Electronics (Op. Amp. Circuits: Active Filters, Amplifiers)

Digital Signal Processing Fundamentals

Working knowledge of a high-level programming language like C or MATLAB (or equivalent simulation environment)

 

Tentative Course Outline:

 

I.                    Introduction: Digital Signal Processing in Medicine

 

 

II.                 Brief Review of the Fundamentals of Discrete-Time Signals and Systems

a.       Concepts of System, Signal, Sequence

b.       The Sampling Process

c.       Impulse Response and Convolution to characterize systems

d.       Z-Ttransform, Discrete Transfer Function

e.       Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT)

 

III.               Electrophysiology of Excitable Cells and Surface Electrical Measurements

a.       Central Nervous System (CNS) Neuron

b.       Information processing in the CNS neuron: Synapses

c.       Action Potentials and the currents they induce

d.       Volume conduction / Voltage measurements at the surface of the body

 

IV.              The Electroencephalogram (EEG)

a.       Recording Techniques

b.       Applications

c.       Artifacts in EEG

d.       Spectral Methods

e.       Time-Frequency Analysis

 

V.                 Evoked Potentials

a.       Types

b.       Noise Characteristic

c.       Multi-trial Noise-Reduction Techniques

d.       Single-Trial Analysis

 

 

VI.              The Electromyogram (EMG)

a.       Generation of electrical changes during muscle contraction

b.       Recording Techniques and Applications

c.       Amplitude and Power estimation of EMG signals

d.       Time delay estimation in EMG signals

e.       Modeling and decomposition of the EMG signal

 

 

VII.            The Electrocardiogram (ECG)

a.       ECG Generation and Recording

b.       Heart Rhythms

c.       Heartbeat Morphologies

d.       Clinical Applications

e.       Baseline Wander

f.        Power line Interference

g.       QRS Detection

h.       Data Compression

i.         Heart Rate Variability (HRV)

 

 

Grading:

 

In-class test                                                                              30%

Individual Project 1                                                                    20%

Individual Project 2                                                                    25%

Term Project (individual or teams of 2)                                       25%

 

Total Points                                                                                100%

 

96 <= A <= 100;                  94<= A- < 96;                          88 <= B+ < 94;                   84 <= B < 88

80 <= B- < 84;                     76 <= C+ < 80;                        72 <= C < 76;                      68 <= C- < 72

65 <= D+ < 68;                    62<= D < 65;                           60 <= D- < 62                     F: Below 60

 

References:

 

Textbook:

1)   Bioelectrical Signal Processing in Cardiac and Neurological Applications

                        by Leif Sornmo and Pablo Laguna

                        Academic Press

ISBN: 0-12-437552-9; (2005)

Suggested:

 

1)      Biomedical Digital Signal Processing,

Willis J. Tompkins, editor. Prentice-Hall, 1993.

ISBN: 0-13-067216-5

 

2) Medical Instrumentation, Application and Design, Third Edition

John G. Webster, editor.

JohnWiley & Sons, 1998. ISBN 0-471-15368-0

 

3) Biomedical Signal Processing and Signal Modeling,

Eugene N. Bruce. John Wiley and Sons, 2001.

ISBN: 0-471-34540-7 

 

4)   Biomedical Signal Analysis: A Case Study Approach

                        by Rangaraj M. Rangayyan, Akay Metin (Editor)

                        Wiley Interscience

ISBN: 0471208116; (December 2001)

 

5) First Principles of Discrete Systems and Signal Processing

                        Robert D. Strum & Donald E. Kirk

                        Addison-Wesley Publishing Co., 1989

 

6) Discrete-Time Signal Processing, Second Edition

                        Alan V. Oppenheim & Ronald W. Schafer, with John R. Buck

                        Prentice-Hall Signal Processing Series, 1999, ISBN: 0-13-754920-2

 

SOME ASSIGNMENTS WILL LIKELY REQUIRE PROGRAMMING SIMULATIONS. Working knowledge of a high-level language (C, Fortran, etc.) or a simulation environment (MATLAB, etc.), will be needed for those.

 

NOTES:

 

1) YOU MUST SUBMIT a floppy disk with all the files (m-files, c-source code, executables, etc.) that may be required by the instructor to verify the functionality of all your projects.

 

2)      The instructor may call on you to explain verbally any of your project submission, as part of the process of project evaluation.

 

3)      This course will adhere to the Electrical & Computer Engineering Department Regulations Concerning Incomplete Grades

 

To qualify for an Incomplete, a student:

  1. Must contact the instructor or secretary before or during missed portion of class,
  2. Must be passing the course prior to that part of the course that is not completed.
  3. Must have documented circumstances beyond his/her control.
  4. Must make up the incomplete work through the instructor of the course; and retake the course.
  5. Must see the Instructor. All missed work must be finished before last two weeks of the following term.