This study reports on the accuracy of smartphone sound measurement applications (apps) and whether they can be appropriately employed for occupational noise measurements. A representative sample of smartphones and tablets on various platforms were acquired, more than 130 iOS apps were evaluated but only 10 apps met our selection criteria. Only 4 out of 62 Android apps were tested. The results showed two apps with mean differences of 0.07 dB (unweighted) and −0.52 dB (A-weighted) from the reference values. Two other apps had mean differences within ± 2 dB. The study suggests that certain apps may be appropriate for use in occupational noise measurements.

This follow-up study examines the accuracy of selected smartphone sound measurement applications (apps) using external calibrated microphones. The initial study examined 192 apps on the iOS and Android platforms and found four iOS apps with mean differences of ±2 dB of a reference sound level measurement system. This study evaluated the same four apps using external microphones. The results showed measurements within ±1 dB of the reference. This study suggests that using external calibrated microphones greatly improves the overall accuracy and precision of smartphone sound measurements, and removes much of the variability and limitations associated with the built-in smartphone microphones.

Objectives: To evaluate (1) the accuracy of the International Organization for Standardization (ISO) standard ISO 1999 [(2013), International Organization for Standardization, Geneva, Switzerland] predictions of noise-induced permanent threshold shift (NIPTS) in workers exposed to various types of high-intensity noise levels, and (2) the role of the kurtosis metric in assessing noise-induced hearing loss (NIHL). Design: Audiometric and shift-long noise exposure data were acquired from a population (N = 2,333) of screened workers from 34 industries in China. The entire cohort was exclusively divided into subgroups based on four noise exposure levels (85 ≤ LAeq.8h < 88, 88 ≤ LAeq.8h < 91, 91 ≤ LAeq.8h < 94, and 94 ≤ LAeq.8h ≤ 100 dBA), two exposure durations (D ≤ 10 years and D > 10 years), and four kurtosis categories (Gaussian, low-, medium-, and high-kurtosis). Predicted NIPTS was calculated using the ISO 1999 model for each participant and the actual measured NIPTS was corrected for age and sex also using ISO 1999. The prediction accuracy of the ISO 1999 model was evaluated by comparing the NIPTS predicted by ISO 1999 with the actual NIPTS. The relation between kurtosis and NIPTS was also investigated. Results: Overall, using the average NIPTS value across the four audiometric test frequencies (2, 3, 4, and 6 kHz), the ISO 1999 predictions significantly (p < 0.001) underestimated the NIPTS by 7.5 dB on average in participants exposed to Gaussian noise and by 13.6 dB on average in participants exposed to non-Gaussian noise with high kurtosis. The extent of the underestimation of NIPTS by ISO 1999 increased with an increase in noise kurtosis value. For a fixed range of noise exposure level and duration, the actual measured NIPTS increased as the kurtosis of the noise increased. The noise with kurtosis greater than 75 produced the highest NIPTS. Conclusions: The applicability of the ISO 1999 prediction model to different types of noise exposures needs to be carefully reexamined. A better understanding of the role of the kurtosis metric in NIHL may lead to its incorporation into a new and more accurate model of hearing loss due to noise exposure.

Occupational noise exposure is one of the most frequent hazards present in the workplace; up to 22 million workers have potentially hazardous noise exposures in the US. As a result, noise-induced hearing loss is one of the most common occupational injuries in the United States. Workers in manufacturing, construction, and the military are at the highest risk for hearing loss. Despite the large number of people exposed to high levels of noise at work, many occupations have not been adequately evaluated for noise exposure. The objective of this experiment was to investigate whether or not iOS smartphones and other smart devices (Apple iPhones and iPods) could be used as reliable instruments to measure noise exposures. For this experiment three different types of microphones were tested with a single model of iPod and three generations of iPhones: the internal microphones on the device, a low-end lapel microphone, and a high-end lapel microphone marketed as being compliant with the International Electrotechnical Commission's (IEC) standard for a Class 2-microphone. All possible combinations of microphones and noise measurement applications were tested in a controlled environment using several different levels of pink noise ranging from 60 to 100 dBA. Results were compared to simultaneous measurements made using a Type 1 sound level measurement system. Analysis of variance and Tukey's honest significant difference (HSD) test were used to determine if the results differed by microphone or noise measurement application. Levels measured with external microphones combined with certain noise measurement applications did not differ significantly from levels measured with the Type 1 sound measurement system. Results showed that it may be possible to use iOS smartphones and smart devices, with specific combinations of measurement applications and calibrated external microphones, to collect reliable, occupational noise exposure data under certain conditions and within the limitations of the device. Further research is needed to determine how these devices compare to traditional noise dosimeter under real-world conditions.

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