Headphone Evaluation for App-Based Automated Mobile Hearing Screening

Abstract Introduction With the need for hearing screenings increasing across multiple populations, a need for automated options has been identified. This research seeks to evaluate the hardware requirements for automated hearing screenings using a mobile application. Objective Evaluation of headphone hardware for use with an app-based mobile screening application. Methods For the purposes of this study, hEAR, a Bekesy-based mobile application designed by the research team, was compared with pure tone audiometric tests administered by an audiologist. Both hEAR and the audiologist's test used 7 frequencies (125 Hz, 250 Hz, 500 Hz, 1,000 Hz, 2000 Hz, 4,000 Hz and 8,000 Hz) adopting four different sets of commercially available headphones. The frequencies were regarded as the independent variable, whereas the sound pressure level (in decibels) was the dependent variable. Thirty participants from a university in Texas were recruited and randomly assigned to one of two groups, whose only difference was the order in which the tests were performed. Data were analyzed using a generalized estimating equation model at α = 0.05. Results Findings showed that, when used to collect data with the mobile app, both the Pioneer HDJ-2000 (Pioneer, Bunkyo, Tokyo, Japan) (p> 0.05) and the Sennheiser HD280 Pro (Sennheiser, Wedemark, Hanover, Germany) (p> 0.05) headphones presented results that were not statistically different from the audiologist's data across all test frequencies. Analyses indicated that both headphones had decreased detection probability at 4kHz and 8kHz, but the differences were not statistically significant. Conclusion Data indicate that a mobile application, when paired with appropriate headphones, is capable of reproducing audiologist-quality data.

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Bibliographic Details
Main Authors: Pickens,Adam W., Robertson,Lakshmi Dakuri, Smith,Matthew Lee, Zheng,Qi, Song,Sejun
Format: Digital revista
Language:English
Published: Fundação Otorrinolaringologia 2018
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1809-48642018000400358
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