The application of frequency and time domain kurtosis to the assessment of hazardous noise exposures

Lei, Sheau‐Fang; Ahroon, William A.; Hamernik, Roger P.

doi:10.1121/1.410287

Cited by 55 publications

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“…The experiments described below were designed to test this hypothesis. However, the experimental design also allowed for (a) a replication or reinforcement of earlier results that showed increased trauma produced by nonG exposures relative to equivalent energy G exposures (Hamernik et al, 2003b;Hamernik and Qiu, 2001;Lei et al, 1994); (b) an evaluation of the equal energy principle as it applies to interrupted/intermittent noise exposures Hamernik et al, 2007); and (c) the effect of toughening/conditioning (Miller et al, 1963;Clark et al, 1987;Canlon et al, 1988;Hamernik et al, 2003aHamernik et al, , 1994Hamernik and Ahroon, 1999) on the resultant hearing and sensory cell loss.…”

Section: Introductionmentioning

confidence: 99%

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

Qiu

Hamernik

Davis

2013

The Journal of the Acoustical Society of America

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A series of Gaussian and non-Gaussian equal energy noise exposures were designed with the objective of establishing the extent to which the kurtosis statistic could be used to grade the severity of noise trauma produced by the exposures. Here, 225 chinchillas distributed in 29 groups, with 6 to 8 animals per group, were exposed at 97 dB SPL. The equal energy exposures were presented either continuously for 5 d or on an interrupted schedule for 19 d. The non-Gaussian noises all differed in the level of the kurtosis statistic or in the temporal structure of the noise, where the latter was defined by different peak, interval, and duration histograms of the impact noise transients embedded in the noise signal. Noise-induced trauma was estimated from auditory evoked potential hearing thresholds and surface preparation histology that quantified sensory cell loss. Results indicated that the equal energy hypothesis is a valid unifying principle for estimating the consequences of an exposure if and only if the equivalent energy exposures had the same kurtosis. Furthermore, for the same level of kurtosis the detailed temporal structure of an exposure does not have a strong effect on trauma.

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Section: Introductionmentioning

confidence: 99%

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

Qiu

Hamernik

Davis

2013

The Journal of the Acoustical Society of America

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“…Non-G noise is very common in factories where it is comprised of a background G noise along with embedded high-level transients (impacts or noise bursts). Evidence that noise exposures, including impulse or impact noise, produce greater traumatic effects to the peripheral auditory receptor than the expected damage estimated by the equalenergy hypothesis is available from studies with both animals (Lei et al, 1994;Hamernik and Qiu, 2001) and humans (Thieryand Meyer-Bisch, 1988). Thus, it is evident that an energy metric alone is not sufficient to characterize a non-G noise for the assessment of the effects of noise exposure.…”

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confidence: 99%

Use of the kurtosis statistic in an evaluation of the effects of noise and solvent exposures on the hearing thresholds of workers: An exploratory study

Fuente

Qiu

Zhang

et al. 2018

The Journal of the Acoustical Society of America

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The aim of this exploratory study was to examine whether the kurtosis metric can contribute to investigations of the effects of combined exposure to noise and solvents on human hearing thresholds. Twenty factory workers exposed to noise and solvents along with 20 workers of similar age exposed only to noise in eastern China were investigated using pure-tone audiometry (1000–8000 Hz). Exposure histories and shift-long noise recording files were obtained for each participant. The data were used in the calculation of the cumulative noise exposure (CNE) and CNE adjusted by the kurtosis metric for each participant. Passive samplers were used to measure solvent concentrations for each worker exposed to solvents over the full work shift. Results showed an interaction between noise exposure and solvents for the hearing threshold at 6000 Hz. This effect was observed only when the CNE level was adjusted by the kurtosis metric.

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“…The truth of this statement i s demonstrated in the Lei et al [8] paper in which kurtosis (statistic) metrics in both the time and frequency domains were shown both to rank order the level of hearing trauma and t o reflect the frequency specificity of trauma. These results are a clear indication that, in addition to energy, temporal and peak variables are important determinants of hearing loss.…”

Section: Introductionmentioning

confidence: 97%

“…These stimuli were shown t o exacerbate hearing loss when compared to spectrallyequivalent Gaussian noises of the same energy [8]. The complex noise consisted of a high-level primary impulsive sequence and multiple reflected components superimposed o n…”

Section: Introductionmentioning

confidence: 99%

“…Such metrics can adequately quantify a noise having a steadystate waveform such as a continuous Gaussian noise and can be used to estimate the hazard to hearing from prolonged exposure to such noise. However, there is abundant evidence in the literature [3][4] [8] showing that nonGaussian, nonstationary types of noises having the same energy and spectra as a Gaussian noise but different temporal structures, produce different audiometric and histological effects on the auditory system. Thus, conventional metrics are not adequate for the assessment of hearing hazards from noise exposures whose waveforms have nonGaussian and nonstationary characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Construction of a joint peak-interval histogram using higher-order cumulant-based inverse filtering

Lei

Hamernik

Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181

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Conventional metrics used to quantify signals i n noise/hearing research rely primarily on time-averaged energy and spectral analyses. Such metrics, while appropriate for Gaussian-distributed waveforms, are of limited value in the more complex sound environments encountered i n industrial/military settings that have nonGaussian and nonstationary-distributed waveforms. Recent research has shown that metrics incorporating the temporal characteristics of a waveform are needed to evaluate hazardous acoustic environments for purposes of hearing conservation. The joint peak-interval histogram is a prospective candidate for use i n such an application. This paper shows that the joint peakinterval histogram can be obtained from an estimation of the temporal pattern of a complex noise waveform by using higherorder cumulant-based inverse filtering. INTRODUCTIONConventional metrics, such as the sound pressure level (SPL), and narrow or broadband (weighted) spectral energies, are used to evaluate the potential of an acoustic noise environment to produce a noise-induced hearing loss (NIHL Based upon some of these early data we formulated the working hypothesis that, for the same total energy and spectrum, a high kurtosis noise exposure is more hazardous t o hearing than a Gaussian noise exposure, and that this effect i s frequency dependent. The truth of this statement i s demonstrated in the Lei et al. [8] paper in which kurtosis (statistic) metrics in both the time and frequency domains were shown both to rank order the level of hearing trauma and t o reflect the frequency specificity of trauma. These results are a clear indication that, in addition to energy, temporal and peak variables are important determinants of hearing loss. Since the kurtosis statistics reflects the peak and temporal structure of a nonGaussian noise, an algorithm that would yield these metrics along with peak and interval histograms would be highly desirable elements of a hearing conservation noise measurement system.The fact that both temporal and spectral variables are important is not surprising since the cochlea has evolved into an exquisitely sensitive transducer of nonstationary stochastic signals typified by speech and music. Results such as outlined above have led to efforts to develop additional metrics which incorporate the temporal information inherent in the waveform of a noise. The joint peak-interval histogram, which shows the cumulative distribution of the peak amplitude reflections and timing intervals of the nonGaussian fluctuations in a noise waveform, is a candidate metric for quantifying noise exposures. This metric, in conjunction with conventional energy-based metrics, may prove to be useful i n the evaluation of a noise environment for the protection of hearing. Higher-order cumulant-based filtering can be used t o deconvolve noise waveforms to obtain the requisite amplitude and timing information for the construction of this proposed metric.Complex noises [7], which simulate the nonstationary and nonGaussian character...

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The application of frequency and time domain kurtosis to the assessment of hazardous noise exposures

Cited by 55 publications

References 0 publications

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

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

Use of the kurtosis statistic in an evaluation of the effects of noise and solvent exposures on the hearing thresholds of workers: An exploratory study

Construction of a joint peak-interval histogram using higher-order cumulant-based inverse filtering

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