Objective: To highlight a selection of data that illustrate the need for better descriptors of complex industrial noise environments for use in the protection of hearing.
Design: The data were derived using a chinchilla model. All noise exposures had the same total energy and the same spectrum; that is, they were equal energy exposures presented at an overall 100 dB(A) SPL that differed only in the scheduling of the exposure and the value of the kurtosis, beta(t), a statistical metric. Hearing thresholds were determined before and after noise exposure using the auditory-evoked potential measured from the inferior colliculus in the brain stem. Cochlear damage was estimated from sensory-cell counts (cochleograms).
Results: (1) For equivalent energy and spectra, exposure to a high-kurtosis, non-Gaussian noise produced substantially greater hearing and sensory-cell loss in the chinchilla model than a low-kurtosis, Gaussian noise. (2) beta(t) computed on the amplitude distribution of the noise could clearly differentiate between the effects of Gaussian and non-Gaussian noise environments. (3) beta(t) can order the extent of the trauma as determined by hearing thresholds and sensory-cell loss.
Conclusions: The noise level in combination with the statistical properties of the noise quantified by beta(t) clearly differentiate the effects between both continuous and interrupted and intermittent Gaussian and non-Gaussian noise environments. For the same energy and spectrum, the non-Gaussian environments are clearly the more hazardous. The use of both an energy and kurtosis metric can better predict the hazard of a high-level complex noise than the use of an energy metric alone (as is the current practice). These results point out the need for a new approach to the analysis and quantification of industrial noise for the purpose of hearing conservation practice.