Analysis of wavelet preprocessed auditory brainstem responses with self-organizing feature maps

Author

Lee, R. ; Özdamar, Ö

Author_Institution

Dept. of Biomed. Eng., Miami Univ., Coral Gables, FL, USA

Volume

1

fYear

1999

fDate

1999

Abstract

Auditory brainstem responses (ABR), recorded from several subjects with normal hearing, were used to train several self-organizing networks (SON). The resultant self-organizing feature maps (SOFM), using intra-subject data, showed promising results with respect to classification of ABR into low, mid, high and no-response regions. Although initial training with averaged ABR was lengthy, wavelet preprocessing helped to reduce computational time while retaining the same promising results

Keywords

auditory evoked potentials; medical signal processing; self-organising feature maps; wavelet transforms; computational time reduction; intrasubject data; normal hearing subjects; self-organizing networks training; wavelet preprocessed auditory brainstem responses analysis; Artificial neural networks; Auditory system; Biomedical engineering; Discrete wavelet transforms; Filtering; Finite impulse response filter; Matched filters; Organizing; Testing; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint

Conference_Location

Atlanta, GA

ISSN

1094-687X

Print_ISBN

0-7803-5674-8

Type

conf

DOI

10.1109/IEMBS.1999.802526

Filename

802526