Speech-in-noise screening tests by internet, Part 2: Improving test sensitivity for noise-induced hearing loss

Leensen, M. C. J.; Laat, J. A. P. M. de; Snik, A.F.M.; Dreschler, Wouter A.

doi:10.3109/14992027.2011.595017

Cited by 46 publications

(57 citation statements)

References 37 publications

(59 reference statements)

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“…Leensen et al, 2011b), but deviates from recommendations in ISO 8253-3. Where the standard prescribes ''to base such curves on a sufficiently large number of otologically normal persons of both sexes, aged between 18 and 25 years inclusive and for whom the test material is appropriate'', there was no information available about the puretone audiogram and it could not be verified which subjects were ontologically normal, because the results were collected through the internet.…”

Section: Subjectsmentioning

confidence: 69%

“…SII predictions were performed, in which relevant parameters of filtered noise conditions were varied to predict the effects on SRT for various audiograms. A more detailed description of the SII predictions can be found in Leensen et al (2011b). According to these predictions, LP filtered noises with cut-off frequencies of 1.4 and 1.6 kHz both discriminate well between NH, and HI individuals.…”

Section: Filtering Of the Masking Noise: Enhancing The Sensitivity Fomentioning

confidence: 98%

“…An a priori power analysis indicated that at least 15 subjects per NH and HI group would be necessary in order to attain a power of 80%, assuming a relevant difference in test outcome (SRT) of 2.6 dB SNR between the groups (Leensen et al, 2011b). A loss of subjects (due to non-attendance, drop-out or exclusion) was anticipated.…”

Section: Subjectsmentioning

confidence: 99%

“…The LP filtered masking noises were created according to the methods described by Leensen et al (2011b). First, a broadband stationary masking noise was created, with the same spectral shape as the LTASS of the optimised word material.…”

Section: Filtering Of the Masking Noise: Enhancing The Sensitivity Fomentioning

confidence: 99%

“…Possible adaptions include adjusting the root mean square levels of the words to achieve equal intelligibility, and filtering of the masking noise. Previous work suggested that a test with a spectrally filtered masking noise better distinguishes between normal-hearing (NH) and hearing-impaired (HI) listeners (Leensen et al, 2011b;Jansen et al, 2014;Vlaming et al, 2014). A stationary low-pass (LP) filtered masker stimulates the use of high-frequency speech information, which is advantageous for NH listeners.…”

Section: Introductionmentioning

confidence: 99%

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Laboratory evaluation of an optimised internet-based speech-in-noise test for occupational high-frequency hearing loss screening: Occupational Earcheck

Rashid

Leensen

Laat

et al. 2017

International Journal of Audiology

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Objective: The ''Occupational Earcheck'' (OEC) is a Dutch online self-screening speech-in-noise test developed for the detection of occupational high-frequency hearing loss (HFHL). This study evaluates an optimised version of the test and determines the most appropriate masking noise. Design: The original OEC was improved by homogenisation of the speech material, and shortening the test. A laboratory-based cross-sectional study was performed in which the optimised OEC in five alternative masking noise conditions was evaluated. Study sample: The study was conducted on 18 normal-hearing (NH) adults, and 15 middle-aged listeners with HFHL. Results: The OEC in a low-pass (LP) filtered stationary background noise (test version LP 3: with a cut-off frequency of 1.6 kHz, and a noise floor of À12 dB) was the most accurate version tested. The test showed a reasonable sensitivity (93%), and specificity (94%) and test reliability (intra-class correlation coefficient: 0.84, mean within-subject standard deviation: 1.5 dB SNR, slope of psychometric function: 13.1%/dB SNR). Conclusions: The improved OEC, with homogenous word material in a LP filtered noise, appears to be suitable for the discrimination between younger NH listeners and older listeners with HFHL. The appropriateness of the OEC for screening purposes in an occupational setting will be studied further.

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Section: Subjectsmentioning

confidence: 69%

Section: Filtering Of the Masking Noise: Enhancing The Sensitivity Fomentioning

confidence: 98%

Section: Subjectsmentioning

confidence: 99%

Section: Filtering Of the Masking Noise: Enhancing The Sensitivity Fomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Laboratory evaluation of an optimised internet-based speech-in-noise test for occupational high-frequency hearing loss screening: Occupational Earcheck

Rashid

Leensen

Laat

et al. 2017

International Journal of Audiology

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Preliminary Evaluation of a Novel Language Independent Speech-in-Noise Test for Adult Hearing Screening

Polo

Zanet

Paglialonga

et al. 2020

8th European Medical and Biological Engineering Conference

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This article presents a preliminary evaluation of a novel language independent Speech-in-Noise test for adult screening in terms of Speech Reception Threshold (SRT) estimates and prediction of hearing sensitivity. The test is based on multiple-choice recognition of meaningless Vowel-Consonant-Vowel words and was administered to 26 normal hearing young adults and 58 unscreened adults who also underwent pure-tone audiometry. Receiver operating characteristics were built using the World Health Organization criteria for "slight/mild" and "moderate" hearing loss as gold standards and SRTs as test outcome. Both curves showed very good test performance in predicting success/failure in pure-tone audiometry (area under the curve: 0.79 for "slight/mild" and 0.83 for "moderate" hearing loss). A complete generalized linear model including SRT, age, and their interaction showed that the SRT and the interaction between SRT and age were significant predictors of pure-tone audiometry outcomes, whereas age alone was not a significant predictor of the degree of hearing loss. Moreover, preliminary results from test-retest data showed that the test was reliable in repeated measures (Spearman's rank-order correlation coefficient = 0.72; Cohen's kappa = 0.83 for "slight/mild" and 0.64 for "moderate" hearing loss). Further research is needed to fully assess test performance in a larger sample of participants, also including subjects with higher degrees of hearing loss (e.g. "severe" and "profound").

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Development and Evaluation of a Novel Method for Adult Hearing Screening: Towards a Dedicated Smartphone App

Polo

Zanet

Lenatti

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Towards implementation of adult hearing screening tests that can be delivered via a mobile app, we have recently designed a novel speech-in-noise test based on the following requirements: user-operated, fast, reliable, accurate, viable for use by listeners of unknown native language and viable for testing at a distance. This study addresses specific models to (i) investigate the ability of the test to identify ears with mild hearing loss using machine learning; and (ii) address the range of the output levels generated using different transducers. Our results demonstrate that the test classification performance using decision tree models is in line with the performance of validated, language-dependent speechin-noise tests. We observed, on average, 0.75 accuracy, 0.64 sensitivity and 0.81 specificity. Regarding the analysis of output levels, we demonstrated substantial variability of transducers' characteristics and dynamic range, with headphones yielding higher output levels compared to earphones. These findings confirm the importance of a self-adjusted volume option. These results also suggest that earphones may not be suitable for test execution as the output levels may be relatively low, particularly for subjects with hearing loss or for those who skip the volume adjustment step. Further research is needed to fully address test performance, e.g. testing a larger sample of subjects, addressing different classification approaches, and characterizing test reliability in varying conditions using different devices and transducers.

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Speech-in-noise screening tests by internet, Part 2: Improving test sensitivity for noise-induced hearing loss

Abstract: The use of low-pass filtered masking noise makes speech-in-noise tests more sensitive to detect NIHL in an early stage.

Cited by 46 publications

References 37 publications

Laboratory evaluation of an optimised internet-based speech-in-noise test for occupational high-frequency hearing loss screening: Occupational Earcheck

Laboratory evaluation of an optimised internet-based speech-in-noise test for occupational high-frequency hearing loss screening: Occupational Earcheck

Preliminary Evaluation of a Novel Language Independent Speech-in-Noise Test for Adult Hearing Screening

Development and Evaluation of a Novel Method for Adult Hearing Screening: Towards a Dedicated Smartphone App

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