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Updated: Mar 24, 2026

Infant Auditory Processing and Event-related Brain Oscillations
Published on: July 1, 2015
Time-frequency decomposition of click evoked otoacoustic emissions in children
Srikanta K Mishra1, Milan Biswal2
1Department of Special Education and Communication Disorders, New Mexico State University, Las Cruces, USA.
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.
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