Literature DB >> 20575723

Hearing assessment-reliability, accuracy, and efficiency of automated audiometry.

De Wet Swanepoel1, Shadrack Mngemane, Silindile Molemong, Hilda Mkwanazi, Sizwe Tutshini.   

Abstract

OBJECTIVE: This study investigated the reliability, accuracy, and time efficiency of automated hearing assessment using a computer-based telemedicine-compliant audiometer.
MATERIALS AND METHODS: Thirty normal-hearing subjects and eight hearing-impaired subjects were tested with pure-tone air conduction audiometry (125-8,000 Hz) in a manual and automated configuration in a counterbalanced manner. For the normal-hearing group each test was repeated to determine test-retest reliability and recording time, and preference for threshold-seeking method (manual vs. automated) was documented.
RESULTS: Test-retest thresholds were not significantly different for manual and automated testing. Manual audiometry test-retest correspondence was 5 dB or less in 88% of thresholds compared to 91% for automated audiometry. Thresholds for automated audiometry did not differ significantly from manual audiometry with 87% of thresholds in the normal-hearing group and 97% in the hearing-impaired group, corresponding within 5 dB or less of each other. The largest overall average absolute difference across frequencies was 3.6 +/- 3.9 dB for the normal-hearing group and 3.3 +/- 2.4 for the hearing-impaired group. Both techniques were equally time efficient in the normal-hearing population, and 63% of subjects preferred the automated threshold-seeking method.
CONCLUSIONS: Automated audiometry provides reliable, accurate, and time-efficient hearing assessments for normal-hearing and hearing-impaired adults. Combined with an asynchronous telehealth model it holds significant potential for reaching underserved areas where hearing health professionals are unavailable.

Entities:  

Mesh:

Year:  2010        PMID: 20575723     DOI: 10.1089/tmj.2009.0143

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  29 in total

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Authors:  Odile H Clavier; James A Norris; David W Hinckley; William Hal Martin; Shi Yuan Lee; Sigfrid D Soli; Douglas S Brungart; Jaclyn R Schurman; Erik Larsen; Golbarg Mehraei; Tera M Quigley
Journal:  J Acoust Soc Am       Date:  2022-07       Impact factor: 2.482

6.  Distortion Product Otoacoustic Emissions in Screening for Early Stages of High-frequency Hearing Loss in Adolescents.

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7.  Online Machine Learning Audiometry.

Authors:  Dennis L Barbour; Rebecca T Howard; Xinyu D Song; Nikki Metzger; Kiron A Sukesan; James C DiLorenzo; Braham R D Snyder; Jeff Y Chen; Eleanor A Degen; Jenna M Buchbinder; Katherine L Heisey
Journal:  Ear Hear       Date:  2019 Jul/Aug       Impact factor: 3.570

8.  Tablet-Based Hearing Test Among Child Clinical Populations: Performance and Preference.

Authors:  Kyoko Nagao; Alexa S Bullard; Lauren E Pasko; Olivia Pereira; Cassidy Walter; Mackenzie Hammond; Jenna Pellicori-Curry; Thierry Morlet
Journal:  Telemed J E Health       Date:  2018-10-25       Impact factor: 3.536

9.  Fast, Continuous Audiogram Estimation Using Machine Learning.

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Journal:  Ear Hear       Date:  2015 Nov-Dec       Impact factor: 3.570

10.  Self-test web-based pure-tone audiometry: validity evaluation and measurement error analysis.

Authors:  Marcin Masalski; Tomasz Kręcicki
Journal:  J Med Internet Res       Date:  2013-04-12       Impact factor: 5.428

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