BIOENG 1580 Syllabus - University of Pittsburgh

UNIVERSITY OF PITTSBURGH
Department of Bioengineering
BioE 1580 - Biomedical Applications of Signal Processing
Fall Term AY2011
INSTRUCTOR: Prof. Patrick Loughlin, 410 BEH, Tel. (412) 624-9685, Email loughlin@pitt.edu
ASSISTANT INSTRUCTOR: Dr. Arash Mahboobin
CLASS MEETS: Tu, Th, 2:30-3:45 p.m., Rm. G24 BEH
OFFICE HRS: After class; “open door” policy (if my door is open, stop in); and by appointment.
PRE-REQ: BioE 1320 (Bio-Signals and Systems, or an equivalent Linear Systems and Signals course), and
proficiency with Matlab. Students must have a basic understanding of continuous-time signals and systems,
including Fourier analysis, Laplace transforms, and LTI systems theory.
Course Description:
This course provides students with some fundamentals of digital signal processing of time series, via applied
exercises and projects with a focus on medical and biological signal analysis. Material covered includes
sampling and converting signals from continuous-time measurements to discrete-time values, stochastic
(random) vs. deterministic signals, noise removal and digital filtering (IIR, FIR and order-statistic filters), signal
detection, and spectral analysis. Students will apply the methods learned to biomedical signals, selected from a
variety of areas such as cardiovascular, gait and balance, electro-physiological (EEG, EKG, ECoG, etc.) and
neural signal processing, among possible others. Particular application areas may differ depending upon data
availability. Material will be presented from the current literature and a text on the subject. Student
responsibilities include regular homework and matlab assignments, quizzes, exams and “mini-projects” every
few weeks to apply methods to biomedical data and simulations (using matlab).
Text: J. Stuller, An Introduction to Signals and Systems, 2008.
Grading: No make-up exams or quizzes without prior arrangement. Late hw loses 20% per day.
Homework, quizzes 20%
Matlab mini-projects 25%
Midterm exam (10/26) 25%
Final exam (12/16) 30%
Course outline: next page
NOTES:
DEADLINE to WITHDRAW from class (see SSOE Admin, 1 st floor, BEH): 10/29/10
University closed Monday 10/11, Monday classes meet Tues 10/12 this week; no 1580 on 10/12.
Thanksgiving recess Nov. 24-28, 2010
Stay healthy! Swine flu info: http://www.pitt.edu/swine-flu/. Wellness program:
http://www.education.pitt.edu/wellness/. Intramural activities: http://www.intramurals.pitt.edu/
If you have a disability for which you are or may be requesting an accommodation, you are encouraged to
contact both your instructor and Disability Resources and Services, 140 William Pitt Union, 412-648-7890 or
412-383-7355 (TTY) as early as possible in the term. DRS will verify your disability and determine reasonable
accommodations for this course.

Course outline: (tentative/approximate, except for exam dates and due dates)
Week Topics
1. (8/31,9/2) Intro & overview of course. Review of continuous-time linear time-invariant (LTI) systems
theory: impulse and step response, convolution, input-output differential equation description, Fourier,
Laplace, frequency response, transfer function, close-loop (feedback) control systems.
2. (9/7,9) LTI rvw, cont’d. From continuous- to discrete-time: sampling and Nyquist criterion; aliasing and
anti-alias filters: the Butterworth LPF, design specifications for desired attenuation at Nyquist.
3. (9/15,16) From continuous to discrete: Difference equations; linear shift-invariant (LSI) discrete time
systems; the z-transform. LSI system transfer functions
4. (9/21,23) Z transform, cont’d. finite-impulse response (FIR) and infinite-impulse response (IIR)
systems. Inverse systems; All-pole (AR) & all-zero (MA) systems.
5. (9/28,30) Z-transform, cont’d. Converting from s-domain to z-domain and vice versa. Forward and
backward rectangular rule; bilinear transform; impulse invariance. Control systems. Matlab project 1
assigned 9/30: Human balance and postural control.
6. (10/5,7) Discrete Fourier analysis: Frequency response, DTFT, DFT, relations to FT.
7. (10/12,14) [No class 10/12 – Monday classes instead.] Discrete Fourier analysis, cont’d. Matlab project
1 due 10/14.
8. (10/19,21) Enhancing / detecting signals in noise: ensemble averaging; filtering; correlation; the
matched filter.
9. (10/26,28) MIDTERM Tues. 10/26. Signal enhancement / detection, cont’d; Matlab project 2 assigned
10/28.
10. (11/2,4) Intro to random signals. Wide-sense stationary signals. Autocorrelation, power spectral density.
Spectral estimation (non-parameteric): periodogram, Welch’s method, windowing.
11. (11/9,11) Spectral estimation, cont’d: parametric AR spectral estimation. Matlab project 2 due 11/11.
12. (11/16,18) Guest lectures by Prof. Aaron Batista, on neural signal processing: spike sorting, pattern
recognition.
13. (11/23) Nonlinear filtering: median and order-statistic filters, applied to eye movement data. Matlab
project 3 assigned 11/23: filtering eye movement (and/or skin blood flow) data.
14. (11/30, 12/2) Order-statistic filters, cont’d. Time-varying spectral analysis: the short-time Fourier
transform (STFT) and spectrogram
15. (12/7,9) Matlab project 3 due 12/7. STFT, spectrogram cont’d. Course wrap-up: Q&A, review.
16. (12/16) FINAL EXAM, Thursday 12/16, 12:00-1:50pm, in classroom (G24)