HEARING HAZARD ASSOCIATED WITH INDUSTRIAL NOISE EXPOSURE

与工业噪声暴露相关的听力危害

• 批准号: 6334832
• 负责人: Roger P Hamernik
• 金额: $ 38.27万
• 依托单位: PLATTSBURGH STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-08-01 至 2003-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6334832
• 关键词: biological models; chinchilla; cochlea; environmental stressor; hearing disorders; histology; human data; industry; light microscopy; loudness; military personnel; model design /development; noise biological effect; noise induced deafness; noise pollution; occupational hazard; otoacoustic emission; sound perception; statistics /biometry; vibration perception

DESCRIPTION: (Adapted from Investigator's Abstract) Considering that many industrial and military noise environments are non-Gaussian, and that energy metrics (i.e., a weighted equivalent energy, Leq) commonly used to assess the adverse effects of a noise exposure on hearing are suitable metrics only for Gaussian noise, the investigator proposes to develop and test the validity of an alternate approach to noise analysis for the purpose of hearing conservation which will more precisely predict the audiometric and morphological consequences of an exposure. Specifically, the investigator will show that an energy metric in combination with the statistical metrics of frequency- and time-domain kurtosis and the joint peak-interval histogram will provide necessary (and possibly sufficient) information on essentially any industrial noise environment to evaluate its potential for causing hearing loss. Animals (chinchillas) will be exposed to non-Gaussian, non-stationary noises having the same energy and spectra of a Gaussian reference noise (two reference noise conditions will be used having spectral and level parameters typical of an industrial environment). Noise stimuli designed with very specific but diverse statistical properties will be produced using recently-designed software. New analytical methods developed in the investigator's laboratories over the past three years involving the wavelet transform and higher-order cumulant-based inverse filtering will be applied to the continuously sampled noise stimuli to extract temporal and peak statistical properties of the noise stimulus. Effects on hearing, quantified by pure-tone thresholds, otoacoustic emissions, and sensory cell losses will be correlated with the noise metrics to establish the validity of these metrics. Considering that the algorithms for the analytical methods mentioned above have been developed and can be integrated into commercial noise analysis systems, the successful outcome of these experiments can lay the foundations for a new and more generalized approach, as well as a more accurate approach to the evaluation of noise environments. The suggested analytical methods may also have some engineering applications in identifying features of the noise environment that can be reduced or altered at their source. It is important to understand what features of a noise are most hazardous to hearing in order that engineering procedures can be implemented on specific noise-producing components of machinery or designed into hearing protective devices. A database consisting of results from at least 408 subjects run through one of two control or 32 different complex noise exposure conditions will be constructed. A large sample size and a wide variation of exposure parameters are necessary to insure statistical power for the correlations that will be developed. While the experimental methods in this proposal are routine, the demonstration of good correlations between the proposed metrics and hearing loss following realistic and diverse exposure conditions has widespread implications for industrial safety standards and noise measurement systems.

描述：（改编自研究者摘要）考虑到许多 工业和军事噪声环境是非高斯的， 度量（即，加权等效能量，Leq）通常用于评估 噪声暴露对听力的不利影响仅是合适的度量 对于高斯噪声，研究人员建议开发和测试 噪声分析的另一种方法， 听力保护，这将更准确地预测听力， 暴露的形态学后果。 具体来说，调查员 将显示能量度量与统计度量相结合 频域和时域峰度和联合峰值间隔直方图 将提供必要的（可能是足够的）信息， 任何工业噪音环境，以评估其潜在的造成 听力损失 动物（龙猫）将暴露于非高斯， 非平稳噪声具有相同的能量和频谱的高斯 参考噪声（将使用两个参考噪声条件， 和工业环境的典型水平参数）。 噪声刺激 设计具有非常具体但不同的统计特性， 使用最新设计的软件制作。 开发的新分析方法 在过去的三年里，调查人员的实验室里， 小波变换和基于高阶累积量的逆滤波将 应用于连续采样的噪声刺激，以提取时间和 噪声刺激的峰值统计特性。 对听力的影响， 通过纯音听阈、耳声发射和感觉细胞进行量化 损失将与噪声度量相关，以建立有效性 这些指标的重要性。 考虑到用于分析的算法 已经开发了上述方法，并且可以集成到 商业噪声分析系统，这些成功的结果， 实验可以为新的和更通用的方法奠定基础， 以及更准确地评估噪声环境的方法。 所提出的分析方法也具有一定的工程应用价值 在识别噪音环境中可以减少的特征时， 在源头改变。 重要的是要了解一个 噪音对听力危害最大，以便工程程序可以 在机器的特定噪声产生部件上实施，或 设计成听力保护装置。 由结果组成的数据库 从至少408名受试者通过两个对照或32个不同的 将构建复杂的噪声暴露条件。 大样本量 并且曝光参数的宽变化是必要的 统计能力的相关性，将开发。 而 本建议的实验方法都是常规的，论证效果好 建议的指标和听力损失之间的相关性， 现实的和多样化的暴露条件具有广泛的影响， 工业安全标准和噪音测量系统。