Literature DB >> 20370034

Measurement of hearing aid internal noise.

James D Lewis1, Shawn S Goodman, Ruth A Bentler.   

Abstract

Hearing aid equivalent input noise (EIN) measures assume the primary source of internal noise to be located prior to amplification and to be constant regardless of input level. EIN will underestimate internal noise in the case that noise is generated following amplification. The present study investigated the internal noise levels of six hearing aids (HAs). Concurrent with HA processing of a speech-like stimulus with both adaptive features (acoustic feedback cancellation, digital noise reduction, microphone directionality) enabled and disabled, internal noise was quantified for various stimulus levels as the variance across repeated trials. Changes in noise level as a function of stimulus level demonstrated that (1) generation of internal noise is not isolated to the microphone, (2) noise may be dependent on input level, and (3) certain adaptive features may contribute to internal noise. Quantifying internal noise as the variance of the output measures allows for noise to be measured under real-world processing conditions, accounts for all sources of noise, and is predictive of internal noise audibility.

Mesh:

Year:  2010        PMID: 20370034      PMCID: PMC2865704          DOI: 10.1121/1.3327808

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  7 in total

1.  Noise in miniature microphones.

Authors:  Stephen C Thompson; Janice L LoPresti; Eugene M Ring; Henry G Nepomuceno; John J Beard; William J Ballad; Elmer V Carlson
Journal:  J Acoust Soc Am       Date:  2002-02       Impact factor: 1.840

2.  Acceptable noise level as a predictor of hearing aid use.

Authors:  Anna K Nabelek; Melinda C Freyaldenhoven; Joanna W Tampas; Samuel B Burchfiel; Robert A Muenchen
Journal:  J Am Acad Audiol       Date:  2006-10       Impact factor: 1.664

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Authors:  M C Killion
Journal:  J Acoust Soc Am       Date:  1976-02       Impact factor: 1.840

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Authors:  A K Nabelek; F M Tucker; T R Letowski
Journal:  J Speech Hear Res       Date:  1991-06

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Authors:  L W Lee; E R Geddes
Journal:  J Acoust Soc Am       Date:  1998-12       Impact factor: 1.840

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Authors:  J Agnew
Journal:  J Acoust Soc Am       Date:  1997-11       Impact factor: 1.840

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Authors:  R Hellman; E Zwicker
Journal:  J Acoust Soc Am       Date:  1987-11       Impact factor: 1.840

  7 in total
  6 in total

1.  Demodulation of quasi-quadrature interferometric signals for use in the totally implantable hearing aids.

Authors:  Milos C Tomic; Zoran V Djinovic; Slobodan J Petricevic
Journal:  Biomed Opt Express       Date:  2017-06-23       Impact factor: 3.732

2.  Effect of Noise Reduction on Cortical Speech-in-Noise Processing and Its Variance due to Individual Noise Tolerance.

Authors:  Subong Kim; Yu-Hsiang Wu; Hari M Bharadwaj; Inyong Choi
Journal:  Ear Hear       Date:  2022 May/Jun       Impact factor: 3.562

3.  Using Objective Metrics to Measure Hearing Aid Performance.

Authors:  James M Kates; Kathryn H Arehart; Melinda C Anderson; Ramesh Kumar Muralimanohar; Lewis O Harvey
Journal:  Ear Hear       Date:  2018 Nov/Dec       Impact factor: 3.570

4.  Listening effort and perceived clarity for normal-hearing children with the use of digital noise reduction.

Authors:  Samantha Gustafson; Ryan McCreery; Brenda Hoover; Judy G Kopun; Pat Stelmachowicz
Journal:  Ear Hear       Date:  2014 Mar-Apr       Impact factor: 3.570

5.  Direct-to-Consumer Hearing Devices: Capabilities, Costs, and Cosmetics.

Authors:  Ibrahim Almufarrij; Kevin J Munro; Piers Dawes; Michael A Stone; Harvey Dillon
Journal:  Trends Hear       Date:  2019 Jan-Dec       Impact factor: 3.293

6.  Clinical use of aided cortical auditory evoked potentials as a measure of physiological detection or physiological discrimination.

Authors:  Curtis J Billings; Melissa A Papesh; Tina M Penman; Lucas S Baltzell; Frederick J Gallun
Journal:  Int J Otolaryngol       Date:  2012-10-08
  6 in total

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