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.