Stimulus frequency otoacoustic emissions (SFOAEs) can have multiple time varying components, including multiple internal reflections. It is, therefore, necessary to study SFOAEs using techniques that can represent their time-frequency behavior. Although various time-frequency schemes can be applied to identify and filter SFOAE components, their accuracy for SFOAE analysis has not been investigated. The relative performance of these methods is important for accurate characterization of SFOAEs that may, in turn, enhance the understanding of SFOAE generation. This study using in silico experiments examined the performance of three linear (short-time Fourier transform, continuous wavelet transform, Stockwell transform) and two nonlinear (empirical mode decomposition and synchrosqueezed wavelet transform) time-frequency approaches for SFOAE analysis. Their performances in terms of phase-gradient delay estimation, frequency specificity, and spectral component extraction are compared, and the relative merits and limitations of each method are discussed. Overall, this paper provides a comparative analysis of various time-frequency methods useful for otoacoustic emission applications.
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