By Topic

Evaluation of Simple Algorithms for Spectral Parameter Analysis of the Electroencephalogram

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

2 Author(s)
Smith, W.D. ; Biomedical Engineering Program, California State University ; Lager, D.L.

Simple autoregressive moving-average (ARMA) and autoregressive (AR) algorithms were tested for use in spectral parameter analysis (SPA) of the background electroencephalogram (EEG). In studies on simulated EEG, both algorithms successfully extracted estimates of the spectral component parameters, and their performance was relatively independent of assumed model order. The ARMA algorithm was unbiased. The AR algorithm, though biased, was simpler and more precise and, thus, may be the most suitable for on-line use. The test results on simulated data were supported by the successful application of the algorithms to human EEG recorded during surgery.

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:BME-33 ,  Issue: 3 )