Abstract

Reflection-source otoacoustic emission phase-gradient delays are widely used to obtain noninvasive estimates of cochlear function and properties, such as the sharpness of mechanical tuning and its variation along the length of the cochlear partition. Although different data-processing strategies are known to yield different delay estimates and trends, their relative reliability has not been established. This paper uses in silico experiments to evaluate six methods for extracting delay trends from reflection-source otoacoustic emissions (OAEs). The six methods include both previously published procedures (e.g., phase smoothing, energy-weighting, data exclusion based on signal-to-noise ratio) and novel strategies (e.g., peak-picking, all-pass factorization). Although some of the methods perform well (e.g., peak-picking), others introduce substantial bias (e.g., phase smoothing) and are not recommended. In addition, since standing waves caused by multiple internal reflection can complicate the interpretation and compromise the application of OAE delays, this paper develops and evaluates two promising signal-processing strategies, the first based on time-frequency filtering using the continuous wavelet transform and the second on cepstral analysis, for separating the direct emission from its subsequent reflections. Altogether, the results help to resolve previous disagreements about the frequency dependence of human OAE delays and the sharpness of cochlear tuning while providing useful analysis methods for future studies.

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