Technical Program

Paper Detail

Paper:	ITT-P2.4
Session:	Emerging DSP Applications
Time:	Thursday, May 18, 10:00 - 12:00
Presentation:	Poster
Topic:	Industry Technology Track: Biomedical
Title:	QEEG-BASED CLASSIFICATION WITH WAVELET PACKET AND MICROSTATE FEATURES FOR TRIAGE APPLICATIONS IN THE ER
Authors:	Leslie Prichep, NYU Medical School, United States; Elvir Causevic, Everest Biomedical Instruments, United States; Ronald R. Coifman, Yale University, United States; Robert Isenhart, NYU Medical School, United States; Arnaud Jacquin, Everest Biomedical Instruments, United States; E. Roy John, NYU Medical School, United States; Mauro Maggioni, Yale University, United States; Frederick J. Warner, Plain Sight Systems, United States
Abstract:	We describe methods for the classification of brain state using quantitative analysis of the EEG (QEEG). Neurometric analysis of EEG collected from the 19 standard locations of the International 10-20 System already provides such a tool. In this work we demonstrate the effectiveness of this approach when the available inputs are reduced to a set of five frontal electrodes. This system has applications in certain critical clinical care situations, such as emergency room triage, when a full EEG might be unavailable, inconvenient, or time-consuming. Additionally, we augment the standard neurometric QEEG analysis with local discriminant basis features of the power spectrum and microstate-like features which exploit the rich temporal structure of the EEG. These enhancements provide clear gains in sensitivity and specificity on a representative database.