Literature DB >> 26976693

Time-frequency decomposition of click evoked otoacoustic emissions in children.

Srikanta K Mishra1, Milan Biswal2.   

Abstract

Determining the time-frequency distributions of click-evoked otoacoustic emissions (CEOAEs) are scientifically and clinically relevant because of their relationship with cochlear mechanisms. This study investigated the time-frequency properties of CEOAEs in 5-10 year old children. In the first part, we examined the feasibility of the S transform to characterize the time-frequency features of CEOAEs. A synthetic signal with known gammatones was analyzed using the S transform, as well as a wavelet transform with the basis function used traditionally for CEOAE analysis. The S and wavelet transforms provided similar representations of the gammatones of the synthetic signal in the mid and high frequencies. However, the S transform yielded a slightly more precise time-frequency representation at low frequencies (500 and 707 Hz). In the second part, we applied the S transform to compare the time-frequency distribution of CEOAEs between adults and children. Several confounding variables, such as spontaneous emissions and potential efferent effects from the use of higher click rates, were considered for obtaining reliable CEOAE recordings. The results revealed that the emission level, level versus frequency plot, latency, and latency versus frequency plot in 5-10 year old children are adult-like. The time-frequency characteristics of CEOAEs in 5-10 year old children are consistent with the maturation of various aspects of cochlear mechanics, including the basal to apical transition. In sum, the description of the time-frequency features in children and the use of the S transform to decompose CEOAEs, are novel aspects of this study. The S transform can be used as an alternative approach to characterize the time-frequency distribution of CEOAEs.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  CEOAE latency; CEOAE level; Click evoked otoacoustic emissions; S transform; Time–frequency distribution; Wavelet transform

Mesh:

Year:  2016        PMID: 26976693     DOI: 10.1016/j.heares.2016.03.003

Source DB:  PubMed          Journal:  Hear Res        ISSN: 0378-5955            Impact factor:   3.208


  8 in total

1.  Comparison of time-frequency methods for analyzing stimulus frequency otoacoustic emissions.

Authors:  Milan Biswal; Srikanta K Mishra
Journal:  J Acoust Soc Am       Date:  2018-02       Impact factor: 1.840

2.  Swept-tone stimulus-frequency otoacoustic emissions: Normative data and methodological considerations.

Authors:  Carolina Abdala; Yeini C Guardia; Christopher A Shera
Journal:  J Acoust Soc Am       Date:  2018-01       Impact factor: 1.840

3.  Efferent-induced alterations in distortion and reflection otoacoustic emissions in children.

Authors:  Srikanta K Mishra; Milan Biswal; Anup Amatya
Journal:  J Acoust Soc Am       Date:  2018-02       Impact factor: 1.840

4.  The role of efferents in human auditory development: efferent inhibition predicts frequency discrimination in noise for children.

Authors:  Srikanta K Mishra
Journal:  J Neurophysiol       Date:  2020-05-20       Impact factor: 2.714

5.  Reflection- and Distortion-Source Otoacoustic Emissions: Evidence for Increased Irregularity in the Human Cochlea During Aging.

Authors:  Carolina Abdala; Amanda J Ortmann; Christopher A Shera
Journal:  J Assoc Res Otolaryngol       Date:  2018-07-02

6.  Sexual Dimorphism in the Functional Development of the Cochlear Amplifier in Humans.

Authors:  Srikanta K Mishra; Samantha Zambrano; Hansapani Rodrigo
Journal:  Ear Hear       Date:  2021 July/Aug       Impact factor: 3.562

7.  Otoacoustic emissions from ears with spontaneous activity behave differently to those without: Stronger responses to tone bursts as well as to clicks.

Authors:  W Wiktor Jedrzejczak; Krzysztof Kochanek; Henryk Skarzynski
Journal:  PLoS One       Date:  2018-02-16       Impact factor: 3.240

8.  Swept-Tone Stimulus-Frequency Otoacoustic Emissions in Human Newborns.

Authors:  Carolina Abdala; Ping Luo; Yeini Guardia
Journal:  Trends Hear       Date:  2019 Jan-Dec       Impact factor: 3.496

  8 in total

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