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

A Procedural Framework for Auditory Steady-State Response Detection

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

4 Author(s)
Van Dun, B. ; Dept. of Neurosciences, Katholieke Univ. Leuven, Leuven ; Rombouts, G. ; Wouters, J. ; Moonen, M.

Auditory steady-state responses (ASSRs) in EEG measurements are currently used for reliable hearing threshold estimation at audiometric frequencies. Especially, newborns with hearing problems benefit from this technique, as with this information, diagnosis can be better specified and hearing aids can be better fitted at an early age. Unfortunately, measurement duration is still very long for clinical widespread use due to the lack of efficient signal detection techniques with sufficient robustness against artifacts. In this paper, a simplified procedural framework for ASSR detection is worked out that allows the development of a multichannel processing strategy, starting from a detection theory approach. It is shown that a sufficient statistic can be calculated that best captures the amount of ASSR in the recorded data. The evaluation is conducted using data from ten normal-hearing adults. It is concluded that most single-and multichannel approaches are similar in performance when applied to uncontaminated EEG. When artifact-rich EEG is used, the proposed detection-theory-based approach significantly improves the number of ASSR detections compared with a noise-weighted common EEG channel derivation (vertex-occiput).

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:56 ,  Issue: 4 )

Date of Publication:

April 2009

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.