Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies.

Auditory signal processing Cochlear synaptopathy Computational modelling Hearing aids Hearing enhancement Hearing loss Peripheral coding Speech intelligibility Temporal-envelope processing

Journal

Hearing research
ISSN: 1878-5891
Titre abrégé: Hear Res
Pays: Netherlands
ID NLM: 7900445

Informations de publication

Date de publication:
10 2022
Historique:
received: 09 05 2022
revised: 07 07 2022
accepted: 12 07 2022
pubmed: 13 8 2022
medline: 28 9 2022
entrez: 12 8 2022
Statut: ppublish

Résumé

It is well known that ageing and noise exposure are important causes of sensorineural hearing loss, and can result in damage of the outer hair cells or other structures of the inner ear, including synaptic damage to the auditory nerve (AN), i.e., cochlear synaptopathy (CS). Despite the suspected high prevalence of CS among people with self-reported hearing difficulties but seemingly normal hearing, conventional hearing-aid algorithms do not compensate for the functional deficits associated with CS. Here, we present and evaluate a number of auditory signal-processing strategies designed to maximally restore AN coding for listeners with CS pathologies. We evaluated our algorithms in subjects with and without suspected age-related CS to assess whether physiological and behavioural markers associated with CS can be improved. Our data show that after applying our algorithms, envelope-following responses and perceptual amplitude-modulation sensitivity were consistently enhanced in both young and older listeners. Speech-in-noise intelligibility showed small improvements after processing but mostly for young normal-hearing participants, with median improvements of up to 8.3%. Since our hearing-enhancement strategies were designed to optimally drive the AN fibres, they were able to improve temporal-envelope processing for listeners both with and without suspected CS. Our proposed algorithms can be rapidly executed and can thus extend the application range of current hearing aids and hearables, while leaving sound amplification unaffected.

Identifiants

pubmed: 35961207
pii: S0378-5955(22)00138-1
doi: 10.1016/j.heares.2022.108569
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

108569

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Auteurs

Fotios Drakopoulos (F)

Hearing Technology Lab, Department of Information Technology, Ghent University, Ghent, Belgium. Electronic address: fotios.drakopoulos@ugent.be.

Viacheslav Vasilkov (V)

Hearing Technology Lab, Department of Information Technology, Ghent University, Ghent, Belgium; Department of Otolaryngology - Head & Neck Surgery, Harvard Medical School, Massachusetts Eye & Ear, Boston, MA, USA.

Alejandro Osses Vecchi (A)

Hearing Technology Lab, Department of Information Technology, Ghent University, Ghent, Belgium; Laboratoire des Systèmes Perceptifs, Département d'Études Cognitives, École Normale Supérieure (ENS), PSL University, Paris, France.

Tijmen Wartenberg (T)

Hearing Technology Lab, Department of Information Technology, Ghent University, Ghent, Belgium; Move the Brain, Zeist, Utrecht, the Netherlands.

Sarah Verhulst (S)

Hearing Technology Lab, Department of Information Technology, Ghent University, Ghent, Belgium.

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Classifications MeSH