Scientific evidence suggests that measurement of otoacoustic emissions (OAE) is a reliable tool to detect the early onset of noise induced hearing loss. Nevertheless, the individual field measurement of otoacoustic emissions on industrial workers is very challenging in practice because the high level of ambient noise usually disturbs the OAE measurement. The use of OAE measurement probes with high passive noise isolation allows the attenuation of most of the high frequency ambient noise, but it is often insufficient for the low frequency content of the ambient noise. In the described research, a new type of OAE system, suitable for the continuous monitoring of OAE levels on an individual worker, has been designed as a pair of earpieces each featuring an external microphone, an internal microphone and a pair of miniature receivers. Adaptive noise reduction (ANR) processing the measured distortion product OAE (DPOAE) is used to further improve the Signal-to-Noise ratio in frequencies mostly where passive isolation remains insufficient. The ANR technique relies on a Normalized Least-Mean-Square (NLMS) algorithm that uses the ipsilateral external microphone and the contralateral internal microphone to denoise the measured DPOAE signals for each in-ear OAE probe. A side-by-side comparison with commercially available clinical OAE equipment on 8 test-subjects successfully confirmed that the developed OAE system would be suitable for the continuous monitoring of workers' hearing capabilities in industrial noise environments with levels up to 75 dB(A).
This study demonstrates that the monitoring of an individual's OAEs could be useful in monitoring temporary changes in hearing status induced by exposure to ambient noise and could be considered as a new tool for effective hearing conservation programs in the workplace.
Objective: To properly measure the effective noise exposure level of workers with hearing protection devices (HPD), the use of in-ear noise dosimeters (IEND) is increasing. Commercial IENDs typically feature one in-ear microphone that captures all noises inside the ear and do not discriminate the residual noise in the earcanal from wearer-induced disturbances (WID) to calculate the in-ear sound pressure levels (SPL). A method to alleviate this particular issue with IENDs and calculate the hearing protection level on-site is therefore proposed. Design: The sound captured by an outer-ear microphone is filtered with the modeled HPD transfer function to estimate the in-ear SPL, this way part of the WIDs mostly captured by the in-ear microphone can be rejected from the SPL. The level of protection provided by the earplugs can then be estimated from the difference between in-ear and outer-ear SPLs. The proposed method is validated by comparing the outcome of the proposed WID rejection method to a reference method. Study sample: The detailed methods are assessed on audio recordings from 16 industrial workers monitored for up to 4 days. Results: The merits of the proposed WID rejection approach are discussed in terms of residual SPL and hearing protection level estimation accuracy. Conclusions: Based on the findings, a method to integrate the proposed WID rejection algorithm in future IENDs is suggested.
Distortion Product Otoacoustic Emissions (DPOAEs) can detect noise-induced hearing loss in-field, but their data extraction is very sensitive to background noise. This paper investigates how passive and active noise reduction enhance DPOAE recording based on data collected in white noise from 54dB(A) to 90dB(A). Despite considerable high-frequency attenuation from a proper placed DPOAE probe, 54dB(A) background noise deteriorates the test outcome substantially. More low-frequency attenuation by an extra passive earmuff enables measurements in white noise levels of 70dB(A). The relationship between external sound level and noise recorded by the DPOAE system has been statistically modeled. Additionally, the upper limits of attenuation improvement are analyzed by quantifying residual physiological noise. Furthermore, for an earplug integrating microphone and speakers of the DPOAE measurement probe, adaptive noise reduction processing on the DPOAE signal is used to improve the Signal-to-Noise ratio. The adaptive noise reduction (ANR) is implemented using the NLMS algorithm to filter out the ambiant noise, measured by the first microphone measuring the DPOAE signal, with a second miniature microphone mounted flush with the external faceplate of the isolating DPOAE probe. Simulated data shows that DPOAE response extraction is possible in an environment with noise levels exceeding 70dB(A).
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