The Hilbert-Huang transform for detection of otoacoustic emissions and time-frequency mapping
(2006) In Informatica 17(1). p.25-38- 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... (More)
- 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 method 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/414500
- author
- Janusauskas, A ; Marozas, V ; Lukosevicius, A and Sörnmo, Leif LU
- organization
- publishing date
- 2006
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- mapping and feature extraction., time-frequency, otoacoustic emission detection, Hilbert-Huang transform
- in
- Informatica
- volume
- 17
- issue
- 1
- pages
- 25 - 38
- publisher
- Slovenian Society Informatika
- external identifiers
-
- wos:000236620800003
- scopus:33645693642
- ISSN
- 0868-4952
- language
- English
- LU publication?
- yes
- id
- 9919656a-b9a3-4738-afed-0f33a8c4ec76 (old id 414500)
- date added to LUP
- 2016-04-01 15:38:35
- date last changed
- 2022-01-28 06:22:02
@article{9919656a-b9a3-4738-afed-0f33a8c4ec76,
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 method 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.}},
author = {{Janusauskas, A and Marozas, V and Lukosevicius, A and Sörnmo, Leif}},
issn = {{0868-4952}},
keywords = {{mapping and feature extraction.; time-frequency; otoacoustic emission detection; Hilbert-Huang transform}},
language = {{eng}},
number = {{1}},
pages = {{25--38}},
publisher = {{Slovenian Society Informatika}},
series = {{Informatica}},
title = {{The Hilbert-Huang transform for detection of otoacoustic emissions and time-frequency mapping}},
volume = {{17}},
year = {{2006}},
}