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https://hdl.handle.net/10356/182685
Title: | Do uHear? Validation of uHear app for preliminary screening of hearing ability in soundscape studies | Authors: | Ong, Zhen-Ting Lam, Bhan Ooi, Kenneth Watcharasupat, Karn N. Wong, Trevor Gan, Woon-Seng |
Keywords: | Engineering | Issue Date: | 2022 | Source: | Ong, Z., Lam, B., Ooi, K., Watcharasupat, K. N., Wong, T. & Gan, W. (2022). Do uHear? Validation of uHear app for preliminary screening of hearing ability in soundscape studies. 24th International Congress on Acoustics (ICA 2022). | Project: | COT-V4-2020-1 | Conference: | 24th International Congress on Acoustics (ICA 2022) | Abstract: | Studies involving soundscape perception often exclude participants with hearing loss to prevent impaired perception from affecting experimental results. Participants are typically screened with pure tone audiometry, the "gold standard" for identifying and quantifying hearing loss at specific frequencies, and excluded if a study-dependent threshold is not met. However, procuring professional audiometric equipment for soundscape studies may be cost-ineffective, and manually performing audiometric tests is labour-intensive. Moreover, testing requirements for soundscape studies may not require sensitivities and specificities as high as that in a medical diagnosis setting. Hence, in this study, we investigate the effectiveness of the uHear app, an iOS application, as an affordable and automatic alternative to a conventional audiometer in screening participants for hearing loss for the purpose of soundscape studies or listening tests in general. Based on audiometric comparisons with the audiometer of 163 participants, the uHear app was found to have high precision (98.04%) when using the World Health Organization (WHO) grading scheme for assessing normal hearing. Precision is further improved (98.69%) when all frequencies assessed with the uHear app is considered in the grading, which lends further support to this cost-effective, automated alternative to screen for normal hearing. | URI: | https://hdl.handle.net/10356/182685 | URL: | https://www.ica2022korea.org/sub_proceedings.php https://ica2022korea.org/ |
DOI (Related Dataset): | 10.21979/N9/JQDI6F | Schools: | School of Electrical and Electronic Engineering | Rights: | © 2022 The Author(s). Published by ICA. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at https://www.ica2022korea.org/sub_proceedings.php. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Conference Papers |
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_ICA22__uHear_Validation.pdf | 1.52 MB | Adobe PDF | ![]() View/Open |
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