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Evaluation of a Novel Speech-in-Noise Test for Hearing Screening: Classification Performance and Transducers’ Characteristics.

Authors :
Zanet, Marco
Polo, Edoardo M.
Lenatti, Marta
van Waterschoot, Toon
Mongelli, Maurizio
Barbieri, Riccardo
Paglialonga, Alessia
Source :
IEEE Journal of Biomedical & Health Informatics; Dec2021, Vol. 25 Issue 12, p4300-4307, 8p
Publication Year :
2021

Abstract

One of the current gaps in teleaudiology is the lack of methods for adult hearing screening viable for use in individuals of unknown language and in varying environments. We have developed a novel automated speech-in-noise test that uses stimuli viable for use in non-native listeners. The test reliability has been demonstrated in laboratory settings and in uncontrolled environmental noise settings in previous studies. The aim of this study was: (i) to evaluate the ability of the test to identify hearing loss using multivariate logistic regression classifiers in a population of 148 unscreened adults and (ii) to evaluate the ear-level sound pressure levels generated by different earphones and headphones as a function of the test volume. The multivariate classifiers had sensitivity equal to 0.79 and specificity equal to 0.79 using both the full set of features extracted from the test as well as a subset of three features (speech recognition threshold, age, and number of correct responses). The analysis of the ear-level sound pressure levels showed substantial variability across transducer types and models, with earphones levels being up to 22 dB lower than those of headphones. Overall, these results suggest that the proposed approach might be viable for hearing screening in varying environments if an option to self-adjust the test volume is included and if headphones are used. Future research is needed to assess the viability of the test for screening at a distance, for example by addressing the influence of user interface, device, and settings, on a large sample of subjects with varying hearing loss. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21682194
Volume :
25
Issue :
12
Database :
Complementary Index
Journal :
IEEE Journal of Biomedical & Health Informatics
Publication Type :
Academic Journal
Accession number :
154074852
Full Text :
https://doi.org/10.1109/JBHI.2021.3100368