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Review
. 2024 Feb 28;24(5):1546.
doi: 10.3390/s24051546.

A Review of Machine Learning Approaches for the Personalization of Amplification in Hearing Aids

Nafisa Zarrin Tasnim  1 , Aoxin Ni  1 , Edward Lobarinas  2 , Nasser Kehtarnavaz  1
Affiliations
Review

A Review of Machine Learning Approaches for the Personalization of Amplification in Hearing Aids

Nafisa Zarrin Tasnim et al. Sensors (Basel). .

Abstract

This paper provides a review of various machine learning approaches that have appeared in the literature aimed at individualizing or personalizing the amplification settings of hearing aids. After stating the limitations associated with the current one-size-fits-all settings of hearing aid prescriptions, a spectrum of studies in engineering and hearing science are discussed. These studies involve making adjustments to prescriptive values in order to enable preferred and individualized settings for a hearing aid user in an audio environment of interest to that user. This review gathers, in one place, a comprehensive collection of works that have been conducted thus far with respect to achieving the personalization or individualization of the amplification function of hearing aids. Furthermore, it underscores the impact that machine learning can have on enabling an improved and personalized hearing experience for hearing aid users. This paper concludes by stating the challenges and future research directions in this area.

Keywords: machine learning approaches to the personalization of hearing aids; personalization of amplification in hearing aids; personalized hearing aid fitting.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Dynamic range of hearing: (i) no hearing loss, (ii) sensorineural hearing loss, and (iii) sensorineural hearing loss with amplification achieved via compression.
Figure 2
Figure 2
Audiogram for a normal hearing case and for a hearing loss case.
Figure 3
Figure 3
Prescription and personalized frequency–response curves indicating sound pressure level (SPL) versus audible frequencies. The range of personalized gains adjustment around prescribed gains across frequency bands is shown by the dashed lines (Maximum and Minimum).
See this image and copyright information in PMC

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