Multiscale detection of transiently evoked otoacoustic emissions

This study presents a novel approach to multiscale detection of transiently evoked otoacoustic emissions. Using statistical hypothesis testing, it is shown that the optimal detector involves a time windowing operation where the window is estimated from ensemble correlation information. The detector performs adaptive splitting of the signal into different frequency bands using wavelet or wavelet packet decomposition. The results show that the presented detectors have performances similar to that of the traditional TEOAE detector, however, the performance improves considerably when the signal energy is disregarded in the threshold test.