Abstract
The elaboration of head-surface registration techniques for auditory potentials evoked from the brainstem (ABR) enabled the construction of objective research and diagnostic methods, which can utilized in the examinations of auditory organs. The aim of the present work was the construction of a method, making use of the neural network techniques, enabling an automated detection of wave V in the ABR signals. The basic problem encountered in any attempts of automated analysis of the auditory potentials is connected with impossibility of a reliable evaluation of a single response evoked by a weak acoustic signal. It has been assumed that considerably better detection results should be obtained, when additional context information will be provided to the network’s input. This assumption has been verified using complex, hybrid neural networks. As a result about 90% of correct recognitions has been achieved
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Izworski, A., Tadeusiewicz, R., Pasławski, A. (2000). The Utilization of Context Signals in the Analysis of ABR Potentials by Application of Neural Networks. In: López de Mántaras, R., Plaza, E. (eds) Machine Learning: ECML 2000. ECML 2000. Lecture Notes in Computer Science(), vol 1810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45164-1_20
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DOI: https://doi.org/10.1007/3-540-45164-1_20
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