By Topic

A layered processing model for knowledge-based contextual interpretation of multichannel EEG/EOG signals

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Chang, T.G. ; Excellence in Inf. Syst. Eng. Center, Tennessee State Univ., Nashville, TN, USA ; Smith, Jack R. ; Principe, J.C.

A layered processing model designed for a knowledge-based expert system for automated classification of multiple channel sleep EEG/EOG (electroencephalogram/electrooculogram) signals is described. A three-layer model is formulated to process and modify the contextual information present in the signal. Each layer is associated with a different processing time frame. It uses a hierarchical architecture that reflects the human expert's information and data abstraction process for the visual inspection of the signal. The model incorporates a certainty handling scheme which uses symbolic representation of certainty levels. The certainty-level information does not participate directly in the rule-execution mechanism, but is manipulated separately and provides augmented information to use effectively for the contextual interpretation in the layered model

Published in:

Southeastcon '88., IEEE Conference Proceedings

Date of Conference:

11-13 Apr 1988