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

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

R Lee and O Ozdamar
Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N, Vol.1, pp.448 vol.1-448
1999
DOI: https://doi.org/10.1109/IEMBS.1999.802526

Abstract

Artificial neural networks Auditory system Biomedical engineering Discrete wavelet transforms Filtering Finite impulse response filter Matched filters Organizing Testing Wavelet analysis
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.

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