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Conference paper

A clinical test battery for Better hEAring Rehabilitation (BEAR): Towards the prediction of individual auditory deficits and hearing-aid benefit

In Proceedings of the 23rd International Congress on Acoustics — 2019, pp. 3841-3848
From

Department of Health Technology, Technical University of Denmark1

Hearing Systems Group, Hearing Systems Section, Department of Health Technology, Technical University of Denmark2

University of Southern Denmark3

One aim of the Better hEAring Rehabilitation (BEAR) project is to define a new clinical profiling tool, a test-battery, for individualized hearing loss characterization. Recently, Sanchez-Lopez et al. (ISAAR 2019) proposed a test battery for hearing deficit characterization. The proposed tests were divided into six categories: audibility, middle-ear analysis, speech perception, binaural-processing abilities, loudness perception, and spectro-temporal resolution.

The results of 54 listeners were analyzed using a data-driven approach (Sanchez-Lopez et al., 2018), which provided evidence for the existence of two independent sources of distortion and four different auditory profiles. The classification of the listeners into auditory profiles allows the prediction of the performance of the listeners on different psychoacoustic tasks as well as their expected performance while wearing hearing aids.

For the classification, a decision tree with only the most predictive tests is desirable for a correct classification of the listeners. The present study aims to explore the optimal decision tree and to propose a reduced, reliable and time-efficient test battery that can classify listeners into the four auditory profiles in a clinical environment.

The clinical test battery will be used in a large-scale study that will help implement a protocol for better hearing rehabilitation.

Language: English
Publisher: Deutsche Gesellschaft für Akustik e.V.
Year: 2019
Pages: 3841-3848
Proceedings: 23rd International Congress on AcousticsInternational Congress on Acoustics
ISBN: 3939296155 and 9783939296157
Types: Conference paper
DOI: 10.18154/RWTH-CONV-239177
ORCIDs: Sanchez Lopez, Raul , Cañete, Oscar , Dau, Torsten and Santurette, Sébastien

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