Hamernik Roger P, Qiu Wei, Davis Bob
Auditory Research Laboratory, State University of New York, 107 Beaumont Hall, Plattsburgh, New York 12901, USA.
J Acoust Soc Am. 2003 Jul;114(1):386-95. doi: 10.1121/1.1582446.
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.
将17组龙猫(每组11至16只动物,总计207只)暴露于100 dB(A)声压级的高斯(G)噪声或16种不同的非高斯(non-G)噪声中的一种,持续5天。所有暴露的总能量相同且频谱大致平坦,但其统计特性有所不同,从而产生了一系列从高斯噪声到各种非高斯条件再到纯冲击噪声暴露的连续变化的暴露条件。通过在原本的高斯噪声中插入高强度瞬态(冲击或噪声脉冲)来产生噪声的非高斯特性。瞬态的峰值声压级、带宽和瞬态间隔各不相同,高斯噪声的均方根电平也有所不同。在未滤波的噪声β(t)上计算的统计量峰度(β)在3≤β(t)≤105范围内变化。使用脑干听觉诱发电位来估计听力阈值,并通过表面制备组织学来确定感觉细胞损失。对于所有非高斯暴露条件,用渐进性和永久性阈值偏移(ATS、PTS)以及感觉细胞损失衡量的损伤都更大。暴露的永久性影响随着β(t)的增加而增加,并在β(t)约为40时达到渐近线。对于β(t)>40,改变间隔或峰值直方图并不会改变损伤程度,这表明在龙猫模型中,对于β(t)>40,能量度量可能有效地评估非高斯噪声环境导致听力损失的可能性。降低瞬态发生的概率可以减少非高斯暴露的永久性影响。这些结果支持了那些使用能量度量来衡量暴露危害的标准文件,但前提是在存在高强度瞬态时应用“校正因子”。在滤波后的噪声信号[β(f)]上计算β可为非高斯噪声提供一个频率特定的度量,该度量与非高斯噪声产生的额外频率特定外毛细胞损失相关。来自丰富多样的暴露条件的数据表明,噪声环境幅度分布的峰度是确定非高斯噪声环境对听力造成危害的一个重要变量。