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Article type: Research Article
Authors: Janušauskas, Artūras | Marozas, Vaidotas | Lukoševičius, Arūnas | Sörnmo, Leif
Affiliations: Biomedical Engineering Institute, Kaunas Technology University, Studentų 65, 51369 Kaunas, Lithuania, e-mail: [email protected] | Signal Processing Group, Lund University, Lund, Sweden
Abstract: This paper presents an application of the Hilbert–Huang transform (HHT) and ensemble correlation for detection of the transient evoked otoacoustic emissions (TEOAEs), and high resolution time–frequency mapping. The HHT provides a powerful tool for nonlinear analysis of nonstationary signals such as TEOAEs. Since the HHT itself does not distinguish between signal and noise it was used with ensemble correlation to extract information about intervals with correlated activity. The combination of methods produced good results for both tasks TEOAE detection and time–frequency mapping. The resulting detection performance, using the mean hearing threshold as audiological separation criterion, was a specificity of 81% at a sensitivity of 90% to be compared to 65% with the traditional wave reproducibility detection criterion. High resolution time frequency mapping predicted in more than 70% of the cases hearing loss at a specific frequency in cases of ski-sloping audiograms. The present m ethod does not require a priori information on the signal and may, with minor changes, be successfully applied to analysis of other types of repetitive signals such as evoked potentials.
Keywords: otoacoustic emission detection, Hilbert–Huang transform, time–frequency mapping and feature extraction
Journal: Informatica, vol. 17, no. 1, pp. 25-38, 2006
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