Investigations of Auditory Filters Based Excitation Patterns for Assessment of Noise Induced Hearing Loss

Noise induced hearing loss (NIHL) as one of major avoidable occupational related health issues has been studied for decades. To assess NIHL, the excitation pattern (EP) has been considered as one of mechanisms to estimate movements of basilar membrane (BM) in cochlea. In this study, two auditory filters, dual resonance nonlinear (DRNL) filter and rounded-exponential (ROEX) filter, have been applied to create two EPs, referring as the velocity EP and the loudness EP, respectively. Two noise hazard metrics are also proposed based on the developed EPs to evaluate hazardous levels caused by different types of noise. Moreover, Gaussian noise and pure-tone noise have been simulated to evaluate performances of the developed EPs and noise metrics. The results show that both developed EPs can reflect the responses of BM to different types of noise. For Gaussian noise, there is a frequency shift between the velocity EP and the loudness EP. For pure-tone noise, both EPs can reflect the frequencies of input noise accurately. The results suggest that both EPs can be potentially used for assessment of NIHL

Investigations of Auditory Filters Based Excitation Patterns for Assessment of Noise Induced Hearing Loss

Noise induced hearing loss (NIHL) as one of major avoidable occupational related health issues has been studied for decades. To assess NIHL, the excitation pattern (EP) has been considered as one of mechanisms to estimate movements of basilar membrane (BM) in cochlea. In this study, two auditory filters, dual resonance nonlinear (DRNL) filter and rounded-exponential (ROEX) filter, have been applied to create two EPs, referring as the velocity EP and the loudness EP, respectively. Two noise hazard metrics are also proposed based on the developed EPs to evaluate hazardous levels caused by different types of noise. Moreover, Gaussian noise and pure-tone noise have been simulated to evaluate performances of the developed EPs and noise metrics. The results show that both developed EPs can reflect the responses of BM to different types of noise. For Gaussian noise, there is a frequency shift between the velocity EP and the loudness EP. For pure-tone noise, both EPs can reflect the frequencies of input noise accurately. The results suggest that both EPs can be potentially used for assessment of NIHL

Comparison of New Metrics for Assessment of Risks of Occupational Noise

Noise induced hearing loss (NIHL) is one of the most common occupational related health problems worldwide. Exposure to excessive noise is the major avoidable cause of permanent hearing loss. The conventional metrics for noise evaluation cannot accurately assess the exposure risks to high-level complex noise, which commonly occurs in many industrial and military fields. Recently, we have developed two advanced models, an adaptive weighting (F-weighting) and a complex velocity level (CVL) auditory fatigue model, to evaluate the risks of occupational noise. In this study, we compared performances of five noise assessment metrics, including F-weighted sound pressure level (SPL) LFeq, CVL model based SPL LCVL, equivalent SPL Leq, A-weighted SPL LAeq, and C-weighted SPL LCeq, using animal experimental data. The animal data includes 22 groups of chinchillas exposed to different types of noise (e.g., Gaussian and non-Gaussian noises). Linear regression analysis is applied to evaluate the correlations between the five noise metrics and the chinchillas’ NIHL data. The results show that both developed F-weighting and CVL models have high corrections with animal hearing loss data compared with the conventional noise metrics (i.e., Leq, LAeq and LCeq). It indicates that both developed models could provide accurate assessment of risks of high-level occupational noise in military and industrial applications. The results also suggest that the CVL model is more accurate than the F-weighting model on assessment of occupational noise

DEVELOPMENT AND VALIDATION OF NEW MODELS AND METRICS FOR THE ASSESSMENTS OF NOISE-INDUCED HEARING LOSS

Noise-induced hearing loss (NIHL) is one of the most common illnesses that is frequently reported in the occupational and military sectors. Hearing loss due to high noise exposure is a major health problem with economic consequences. Industrial and military noise exposures often contain high-level impulsive noise components. The presence of these impulsive noise components complicates the assessment of noise levels for hearing conservation purposes. The current noise guidelines use equal energy hypothesis (EEH) based metrics to evaluate the risk of hearing loss. A number of studies show that the current noise metrics often underestimates the risk of hearing loss in high-level complex noise environments. The overarching goal of this dissertation is to develop advance signal processing based methods for more accurate assessments of the risk of NIHL. For these assessments, various auditory filters that take into account the physiological characteristics of the ear are used. These filters will help to understand the complexity of the ear’s response to high-level complex noises

Fatigue Modeling via Mammalian Auditory System for Prediction of Noise Induced Hearing Loss

Noise induced hearing loss (NIHL) remains as a severe health problem worldwide. Existing noise metrics and modeling for evaluation of NIHL are limited on prediction of gradually developing NIHL (GDHL) caused by high-level occupational noise. In this study, we proposed two auditory fatigue based models, including equal velocity level (EVL) and complex velocity level (CVL), which combine the high-cycle fatigue theory with the mammalian auditory model, to predict GDHL. The mammalian auditory model is introduced by combining the transfer function of the external-middle ear and the triple-path nonlinear (TRNL) filter to obtain velocities of basilar membrane (BM) in cochlea. The high-cycle fatigue theory is based on the assumption that GDHL can be considered as a process of long-cycle mechanical fatigue failure of organ of Corti. Furthermore, a series of chinchilla experimental data are used to validate the effectiveness of the proposed fatigue models. The regression analysis results show that both proposed fatigue models have high corrections with four hearing loss indices. It indicates that the proposed models can accurately predict hearing loss in chinchilla. Results suggest that the CVL model is more accurate compared to the EVL model on prediction of the auditory risk of exposure to hazardous occupational noise