Literature DB >> 12880050

The effects of the amplitude distribution of equal energy exposures on noise-induced hearing loss: the kurtosis metric.

Roger P Hamernik1, Wei Qiu, Bob Davis.   

Abstract

Seventeen groups of chinchillas with 11 to 16 animals/group (sigmaN = 207) were exposed for 5 days to either a Gaussian (G) noise or 1 of 16 different non-Gaussian (non-G) noises at 100 dB(A) SPL. All exposures had the same total energy and approximately the same flat spectrum but their statistical properties were varied to yield a series of exposure conditions that varied across a continuum from G through various non-G conditions to pure impact noise exposures. The non-G character of the noise was produced by inserting high level transients (impacts or noise bursts) into the otherwise G noise. The peak SPL of the transients, their bandwidth, and the intertransient intervals were varied, as was the rms level of the G noise. The statistical metric, kurtosis (beta), computed on the unfiltered noise beta(t), was varied 3 < or = beta(t) < or = 105. Brainstem auditory evoked responses were used to estimate hearing thresholds and surface preparation histology was used to determine sensory cell loss. Trauma, as measured by asymptotic and permanent threshold shifts (ATS, PTS) and by sensory cell loss, was greater for all of the non-G exposure conditions. Permanent effects of the exposures increased as beta(t) increased and reached an asymptote at beta(t) approximately 40. For beta(t) > 40 varying the interval or peak histograms did not alter the level of trauma, suggesting that, in the chinchilla model, for beta(t) > 40 an energy metric may be effective in evaluating the potential of non-G noise environments to produce hearing loss. Reducing the probability of a transient occurring could reduce the permanent effects of the non-G exposures. These results lend support to those standards documents that use an energy metric for gauging the hazard of exposure but only after applying a "correction factor" when high level transients are present. Computing beta on the filtered noise signal [beta(f)] provides a frequency specific metric for the non-G noises that is correlated with the additional frequency specific outer hair cell loss produced by the non-G noise. The data from the abundant and varied exposure conditions show that the kurtosis of the amplitude distribution of a noise environment is an important variable in determining the hazards to hearing posed by non-Gaussian noise environments.

Entities:  

Mesh:

Year:  2003        PMID: 12880050     DOI: 10.1121/1.1582446

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


  14 in total

Review 1.  Occupational Hearing Loss from Non-Gaussian Noise.

Authors:  Alice H Suter
Journal:  Semin Hear       Date:  2017-07-19

2.  The value of a kurtosis metric in estimating the hazard to hearing of complex industrial noise exposures.

Authors:  Wei Qiu; Roger P Hamernik; Robert I Davis
Journal:  J Acoust Soc Am       Date:  2013-05       Impact factor: 1.840

3.  Kurtosis corrected sound pressure level as a noise metric for risk assessment of occupational noises.

Authors:  G Steven Goley; Won Joon Song; Jay H Kim
Journal:  J Acoust Soc Am       Date:  2011-03       Impact factor: 1.840

4.  Estimation of Occupational Noise-Induced Hearing Loss Using Kurtosis-Adjusted Noise Exposure Levels.

Authors:  Meibian Zhang; Xiangjing Gao; William J Murphy; Chucri A Kardous; Xin Sun; Weijiang Hu; Wei Gong; Jingsong Li; Wei Qiu
Journal:  Ear Hear       Date:  2022-04-21       Impact factor: 3.562

5.  Analysis of environmental sound levels in modern rodent housing rooms.

Authors:  Amanda M Lauer; Bradford J May; Ziwei Judy Hao; Julie Watson
Journal:  Lab Anim (NY)       Date:  2009-05       Impact factor: 12.625

6.  Noise-induced hearing loss and its prevention: Integration of data from animal models and human clinical trials.

Authors:  Colleen G Le Prell; Tanisha L Hammill; William J Murphy
Journal:  J Acoust Soc Am       Date:  2019-11       Impact factor: 1.840

7.  The Use of the Kurtosis-Adjusted Cumulative Noise Exposure Metric in Evaluating the Hearing Loss Risk for Complex Noise.

Authors:  Hong-Wei Xie; Wei Qiu; Nicholas J Heyer; Mei-Bian Zhang; Peng Zhang; Yi-Ming Zhao; Roger P Hamernik
Journal:  Ear Hear       Date:  2016 May-Jun       Impact factor: 3.570

8.  New Metrics Needed in the Evaluation of Hearing Hazard Associated With Industrial Noise Exposure.

Authors:  Meibian Zhang; Hongwei Xie; Jiena Zhou; Xin Sun; Weijiang Hu; Hua Zou; Lifang Zhou; Jingsong Li; Ming Zhang; Chucri A Kardous; Thais C Morata; William J Murphy; Jane Hongyuan Zhang; Wei Qiu
Journal:  Ear Hear       Date:  2021 Mar/Apr       Impact factor: 3.562

9.  Threshold for onset of injury in Chinook salmon from exposure to impulsive pile driving sounds.

Authors:  Michele B Halvorsen; Brandon M Casper; Christa M Woodley; Thomas J Carlson; Arthur N Popper
Journal:  PLoS One       Date:  2012-06-20       Impact factor: 3.240

10.  Software-based noise reduction in cranial magnetic resonance imaging: Influence on image quality.

Authors:  Philipp Fuelkell; Soenke Langner; Nele Friedrich; Marie-Luise Kromrey; Christoph G Radosa; Ivan Platzek; Birger Mensel; Jens-Peter Kühn
Journal:  PLoS One       Date:  2018-11-01       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.