Title :
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
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;
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
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.802526