Brief Tutorial Description:
This tutorial presents the definitions, concepts, and background needed
to understand fuzzy logic and why it is so popular, especially
regarding biomedical applications. It discusses fuzzy system design
considerations, methods, and validation. Two examples are presented:
one example works through the process of fuzzy inference from start to
finish; the other elucidates how the concept of partial set membership
facilitated a biomedical data mining application that simply could not
have been implemented using traditional approaches. Lastly, some
conceptual biomedical applications are presented to illustrate future
directions for fuzzy systems.
Ms. O Brien earned her B.S. in electrical engineering in 1987 from the
University of Delaware and her M.S. in electrical engineering in 1991
from Loyola College in Baltimore, MD. She is currently an electrical
engineering doctoral student at the George Washington University, where
her dissertation includes a slightly unconventional mix of control
theory, biomedical engineering, and soft computing that focuses on
biomechanical systems modeling and implementing traditional mathematics
in fuzzy logic. Her primary goal is to develop an intuitive, easily
user-modified fuzzy implementation of the A.V. Hill forward dynamics
muscle model. To support her research, she has developed a
full-featured fuzzy inference engine that improves greatly on some
commercial packages ( Fuzzy Inference Engine Provides Opportunity for
Testbed, IEEE ISCAS Conference Proceedings, May 2002). She plans to
graduate no later than Spring 2004.