Literature DB >> 20179426

Computer-assisted audiometry versus manual audiometry.

Allan Thiam Poh Ho1, Anthony J Hildreth, Leon Lindsey.   

Abstract

OBJECTIVE: The Otogram is an automated computer-assisted audiometer that allows patients to self-administer audiometry for their pure-tone audiogram. There has been no research published in a peer-reviewed journal, validating its use in an otology outpatient clinic. We therefore proposed to investigate and compare the inter-rater and intrarater accuracy and reliability of audiologists and of the Otogram in an English-speaking British population.
DESIGN: Prospective nonrandomized validation study.
SETTING: Secondary otolaryngology center and otology outpatient clinic. PARTICIPANTS: Forty-eight NHS patients referred to an otology outpatient clinic. MAIN OUTCOME MEASURES: Each patient had 2 pure-tone audiograms. Hearing thresholds in decibels hearing level were ascertained by fully trained British audiologists and by the Otogram.
RESULTS: Using the weighted kappa statistic, the level of agreement in air-conduction (kappa = 0.965) and bone-conduction (kappa = 0.927) thresholds between the audiologist and the Otogram on the same patient was equivalent to the inter-rater level of agreement between pairs of audiologists. Approximately 94% of air-conduction thresholds and 91% of bone-conduction thresholds measured by the Otogram fell within 10 dB of thresholds measured by an audiologist. Intrarater comparisons between audiologists were very good for air-conduction (kappa = 0.978) and bone-conduction (kappa = 0.964). The intrarater level of agreement between repeated Otogram thresholds was just as good for air-conduction (kappa = 0.974) and bone-conduction (kappa = 0.945) thresholds.
CONCLUSION: The Otogram is just as reliable as audiologists at determining hearing thresholds. We recommend that the Otogram can be safely used in a controlled clinical setting supervised by audiologists.

Entities:  

Mesh:

Year:  2009        PMID: 20179426     DOI: 10.1097/MAO.0b013e3181b120d0

Source DB:  PubMed          Journal:  Otol Neurotol        ISSN: 1531-7129            Impact factor:   2.311


  11 in total

1.  A self-fitting hearing aid: need and concept.

Authors:  Elizabeth Convery; Gitte Keidser; Harvey Dillon; Lisa Hartley
Journal:  Trends Amplif       Date:  2011-12-04

2.  Threshold measurements by self-fitting hearing aids: feasibility and challenges.

Authors:  Gitte Keidser; Harvey Dillon; Dan Zhou; Lyndal Carter
Journal:  Trends Amplif       Date:  2012-03-07

3.  The Accuracy of IOS Device-based uHear as a Screening Tool for Hearing Loss: A Preliminary Study From the Middle East.

Authors:  Rashid Al-Abri; Mustafa Al-Balushi; Arif Kolethekkat; Deepa Bhargava; Amna Al-Alwi; Hana Al-Bahlani; Manal Al-Garadi
Journal:  Oman Med J       Date:  2016-03

4.  Fast, Continuous Audiogram Estimation Using Machine Learning.

Authors:  Xinyu D Song; Brittany M Wallace; Jacob R Gardner; Noah M Ledbetter; Kilian Q Weinberger; Dennis L Barbour
Journal:  Ear Hear       Date:  2015 Nov-Dec       Impact factor: 3.570

5.  Dynamically Masked Audiograms With Machine Learning Audiometry.

Authors:  Katherine L Heisey; Alexandra M Walker; Kevin Xie; Jenna M Abrams; Dennis L Barbour
Journal:  Ear Hear       Date:  2020 Nov/Dec       Impact factor: 3.562

6.  Hearing Tests on Mobile Devices: Evaluation of the Reference Sound Level by Means of Biological Calibration.

Authors:  Marcin Masalski; Lech Kipiński; Tomasz Grysiński; Tomasz Kręcicki
Journal:  J Med Internet Res       Date:  2016-05-30       Impact factor: 5.428

7.  Hearing Tests Based on Biologically Calibrated Mobile Devices: Comparison With Pure-Tone Audiometry.

Authors:  Marcin Masalski; Tomasz Grysiński; Tomasz Kręcicki
Journal:  JMIR Mhealth Uhealth       Date:  2018-01-10       Impact factor: 4.773

8.  Adult validation of a self-administered tablet audiometer.

Authors:  Mark Bastianelli; Amy E Mark; Arran McAfee; David Schramm; Renée Lefrançois; Matthew Bromwich
Journal:  J Otolaryngol Head Neck Surg       Date:  2019-11-07

Review 9.  Tele-Audiology: Current State and Future Directions.

Authors:  Kristen L D'Onofrio; Fan-Gang Zeng
Journal:  Front Digit Health       Date:  2022-01-10

10.  Sensitivity and Specificity of Automated Audiometry in Subjects with Normal Hearing or Hearing Impairment.

Authors:  Åsa Skjonsberg; Catrine Heggen; Meisere Jamil; Per Muhr; Ulf Rosenhall
Journal:  Noise Health       Date:  2019 Jan-Feb       Impact factor: 0.867

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.