A Hearing-Model-Based Active-Learning Test for the Determination of Dead Regions

Trends in Hearing
Josef SchlittenlacherBrian C J Moore

Abstract

This article describes a Bayesian active-learning procedure for estimating the edge frequency, fe, of a dead region, that is, a region in the cochlea with no or very few functioning inner hair cells or neurons. The method is based on the psychophysical tuning curve (PTC) but estimates the shape of the PTC from the parameters of a hearing model, namely fe, and degree of outer hair cell loss. It chooses the masker frequency and level for each trial to be highly informative about the model parameters in the context of previous data. The procedure was tested using 14 ears from eight subjects previously diagnosed with high-frequency dead regions. The estimates of fe agreed well with estimates obtained using "Fast PTCs" or more extensive measurements from an earlier study. On average, 33 trials were needed for the estimate of fe to fall and stay within 0.3 Cams of the final "true" value on the equivalent rectangular bandwidth-number scale. The time needed to obtain a reliable estimate was 5 to 8 min. This is comparable to the time required for Fast PTCs and short enough to be used when fitting a hearing aid. Compared with Fast PTCs, the new method has the advantage of using yes-no judgments rather than continuous Békésy tracking. Thi...Continue Reading

References

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Citations

Aug 5, 2018·The Journal of the Acoustical Society of America·Josef SchlittenlacherBrian C J Moore

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Methods Mentioned

BETA
cochlear implant

Software Mentioned

Smart
Smart DRT

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