Cart (Loading....) | Create Account
Close category search window
 

Identifying respiratory-related evoked potentials

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)
Lim, L.M. ; Dept. of Physiol., Dartmouth Med. Sch., Hanover, NH, USA ; Akay, M. ; Daubenspek, J.A.

This study further demonstrates that the wavelet approach to the analysis and characterization of respiratory-related evoked potentials (RREPs) is a more efficient method than traditional ensemble averaging. Wavelet decomposition of the 200 trial ensemble averaged evoked responses results in smoothed signals at scale 4 with characteristics similar to those present in the ensemble averages, indicating that the wavelet approach permits accurate estimation of RREPs. Furthermore, subsequent reconstruction from the last 4 scales produces signals nearly identical to the original smoothed responses, demonstrating the validity of the reconstruction process. The wavelet approach is not only useful in the characterization of long term evoked responses, the wavelet estimates of short term (5-, 10-, and 25-trial) evoked responses also show high correspondence to the original signals and contain components similar among short term estimates. The similarities among short term estimates demonstrate that wavelet decomposition of successive short averages produces estimates of the signal that are stable. Although the responses of one subject showed significant and stable components in as few as 10 trials, variations in the level of background EEG activity among subjects may cause slight differences in the minimum number of trials required

Published in:

Engineering in Medicine and Biology Magazine, IEEE  (Volume:14 ,  Issue: 2 )

Date of Publication:

Mar/Apr 1995

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.