Annelies Bockstael, Hannah Keppler, and Dick Botteldooren

Improved hearing conservation in industry: More efficient implementation of distortion product otoacoustic emissions for accurate hearing status monitoring Annelies Bockstael, Hannah Keppler, and Dick Botteldooren Citation: Proc. Mtgs. Acoust. 19, 040018 (2013); View online: https://doi.org/10.1121/1.4800408 View Table of Contents: http://asa.scitation.org/toc/pma/19/1 Published by the Acoustical Society of America

Proceedings of Meetings on Acoustics Volume 19, 2013 http://acousticalsociety.org/ ICA 2013 Montreal Montreal, Canada 2-7 June 2013 Noise Session 1pNSa: Advanced Hearing Protection and Methods of Measurement II 1pNSa10. Improved hearing conservation in industry: More efficient implementation of distortion product otoacoustic emissions for accurate hearing status monitoring Annelies Bockstael*, Hannah Keppler and Dick Botteldooren *Corresponding author's address: Information technology, Ghent University, Sint-Pietersnieuwstraat 41, Ghent, 9000, Oost- Vlaanderen, Belgium, annelies.bockstael@intec.ugent.be Preventing occupational hearing damage requires close monitoring of workers' hearing. Implementing Distortion Product Otoacoustic Emissions (DPOAEs) in-field is a sensitive and feasible approach provided that a combination of minimal measuring time and infrequent falsepositives - i.e. cases where elevated background erroneously compromises DPOAEs - is found. This paper investigates how measurement time can be reduced by carefully selecting the tested frequency span, and how false-positives are minimized by comparing DPOAEs acquired in noise with DPOAE signals previously obtained in optimal test conditions. To test this, DPOAEs have been registered with a 1/8-octave band resolution from 841 Hz to 8000 Hz for 60 subjects, in quiet conditions and in white noise levels ranging from 54 db(a) to 90 db(a), with and without extra noise reduction Within-subject variation of DPOAEs in noisy conditions is assessed at different levels of background noise. Obtained test-retest statistics quantify normal variability and allow within normal working routines to follow-up on persons with DPOAEs falling outside this range. To increase efficiency, optimal frequency regions are addressed by investigating per frequency the intra-subject DPOAE signal variability and DPOAE noise level. Published by the Acoustical Society of America through the American Institute of Physics 2013 Acoustical Society of America [DOI: 10.1121/1.4800408] Received 22 Jan 2013; published 2 Jun 2013 Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 1

INTRODUCTION Occupational hearing conservation programs rely on three major principles; noise reduction, training and education, and hearing status follow-up. When this is put in place using personal hearing protectors, the final outcome entirely depends on the actions and behavior of each individual worker. Hence, a decent framework is needed, including adequate hearing conservation policy [1] and validation of implemented noise reduction measures. Currently, hearing status monitoring is often limited to yearly testing. While the assessment itself might be very thorough, it can by no means prevent that hearing loss builds up unnoticed over months and as such it is not suitable to identify worker-specific risk sources nor does it allow immediate intervention. Therefore, periodic testing should be complemented with more regular screening at the work floor. General principles of standard clinical approaches can be transfered, but implementation and interpretation have to be adapted to more difficult test conditions, so that one can reliable determine whether the worker can continue working as it is, or whether follow-up of hearing status with a more extensive test battery is needed. In this paper, a screening protocol based on distortion-product otoacoustic emissions (DPOAEs) is assessed. This test can detect early signs of noise-induced hearing damage [2] in a quick and non-invasive way [3], but as its results are sensitive to interfering background noise [4], adaptations are needed before it can be implemented in suboptimal test situations. To distinguish true DPOAE signals from artifacts, their amplitude is often compared to the background noise. Exact pass/fail criteria vary between protocols, but in general cut-off values are set at 0 db, 3 db or 6 db signal-to-noise ratio [5]. This makes the assessment by definition very depend on intruding elevated ambient noise and therefore in-field DPOAEs need alternative for signal-to-noise criteria. In this, the idea of long-term monitoring can be adopted, meaning that no absolute assessment of DPOAE amplitude is needed, but rather for a specific individual possibly pathological variation has to be acknowledged. Additionally, in real working conditions, efficient testing becomes one of the major requirements as maximal information needs to be retrieved in a minimal amount of time. With respect to OAE, some frequency regions have been shown to be more robust in suboptimal test conditions, making them more suitable for implementation in screening protocols than others [6]. This paper first systematically investigates the influence of ambient noise on measured DPOAE signal and DPOAE noise. Subsequently, the possibility for accurate screening based on baseline DPOAE results is assessed. Finally, the robustness of different DPOAE frequency regions is dealt with. MATERIAL AND METHOD Test subjects Sixty-two volunteers have been tested, 34 between 18 and 30 years old (17 male, 17 female) and 28 between 31 and 46 years (16 male, 12 female). For each subject, either the right or the left ear has been randomly selected. Tympanometry, otoscopy and tonal audiometry have been carried out to confirm normal hearing status. DPOAE measurements DPOAEs were measured with the ILO 292 USB II hardware and ILO v6 software (Otodynamics Ltd.) coupled with a laptop. The DPOAE probe was calibrated before each measuring session with the 1cc calibration cavity provided by the manufacturer. The most Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 2

Freq (Hz) 63 125 250 500 1000 2000 4000 8000 Mf (db) 14.1 11.6 18.7 27.5 32.9 33.6 36.1 35.8 sf (db) 4.0 4.3 3.6 2.5 2.7 3.4 3.0 3.8 APV (db) 10.1 7.3 15.1 25 30.1 30.2 33.2 32.0 TABLE 1: REAT attenuation data for passive earmuff measured following ISO standard [8], Mf is the average attenuation, sf the standard deviation and APV the Assumed Protection Value. No Noise HPD level [db(a)] quiet quiet no 24.7 54 white no 54.1 58 white no 57.2 62 white no 62.3 70 white yes 70.8 77 white yes 77.7 83 white yes 83.4 90 white yes 90.3 TABLE 2: Overview of test conditions. optimal probe fit in the ear canal was ensured by performing the check-fit procedure by a click stimulus before each measurement. 2f1-f2 DPOAEs were measured with simultaneous presentation of two primary tones using a fixed primary tone level combination of 65 and 55 db SPL respectively for the first and second primary tone. The second primary tone ranged in frequency from 841 Hz to 8000 Hz and was presented at eight points per octave. The ratio of the primary tone frequencies f2/f1 equaled 1.22. A noise artifact rejection level of 8 mpa was used and the measurement was stopped after the complete frequency range had been looped four times. For the DPOAE signals to be included, no a-priori signal-to-noise ratio has been set because assessing different criteria for signal validity is of interest. However, amplitudes exactly equaling the detection floor of the system (in casu -30.0 db) are rejected. Ambient background noise White noise fragments between 54 db(a) and 90 db(a) have been created with Audacity software. Samples have been played in random order per participants using an Adam Audio S1X loudspeaker with built-in amplifier, connected to a laptop PC with an U24XL sound card. The test subject was seated at 78 cm from the loudspeaker, the setup has been calibrated at the beginning of each testing day with a Svantek sound analyzer. For fragments between 70 db(a) and 90 db(a), a Peltor Optime I earmuff has been placed on top of the OAE probe, see Table 1 for the Real Ear At Threshold (REAT) attenuation data provided by the manufacturer. Table 2 gives an overview of all test conditions, the noise levels are recorded at the test subject s position without any subject being present. Per DPOAE response frequency, the results have been coupled with the ambient background noise in the corresponding 1 3-octave band. The frequency resolution of the ambient noise was not further refined to DPOAE frequency resolution (eight points per octave band) to ensure that the results obtained in this project are applicable with standard equipment. In addition, the frequency resolution of the DPOAE was not downscaled to 1 3-octave band because variation of DPOAE signal and DPOAE noise as a function of frequency is of particular interest in this paper. Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 3

Level (db) -10-5 0 5 10 15 20 Signal Noise 54 58 62 70 77 83 90 Q Test condition FIGURE 1: Signal and noise measured by the DPOAE equipment as a function of test condition: baseline condition with no extra background noise ( Q ) and 7 fragments of white noise are included ranging from 54 db(a) to 90 db(a). For the fragments from 70 db(a) to 90 db(a), an earmuff has been placed on top of the OAE probe. RESULTS Influence of background noise on DPOAE signal and noise Figure 1 clearly shows that the DPOAE noise depends much stronger on the ambient background noise than the signal. The DPOAE noise increases as the interfering ambient noise level increases, and the effect of placing an earmuff on top of the OAE probe is easily noticeable with DPOAE noise levels dropping between 62 db(a) (no earmuff) and 70 db(a) (earmuff). The average DPOAE noise level at 70 db(a) almost equals the level in the baseline condition where no extra external noise is added, but the standard deviation is markedly larger. In elevated background noise, exact probe and earmuff placement becomes critical to provide sufficient attenuation, which might vary substantially between subjects. The reader is referred to the accompanying paper [7] for a more in-depth discussion of the relationship between external noise, noise reduction and DPOAE noise. Unlike the DPOAE noise levels, DPOAE signals are much more stable across test condition, except for a small decline in mean signal strength in 90 db(a) white background noise. Additionally, in this condition and for 83 db(a), signal detection fails for more than half of the observations. Hence, despite the use of an earmuff, the current OAE registration setup appears to be unsuitable for accurate DPOAE signal detection in white noise levels of 83 db(a) and more. For the retained test conditions, mixed-model linear regression with signal amplitude as outcome variable, test condition as categorical fixed independent variable and subject as random variable shows no significant variation in DPOAE signal between test conditions (p = 0.44). Here, per subject only those frequencies are taken into account that have present signals in all test conditions, this to ensure that no false effects are introduced by including different observations per test condition. Variation of DPOAE signal in ambient noise Figure 2 illustrates the average signal-to-noise ratio as a function of the stimulus frequency of the second primary tone. While the signal-to-noise ratio is clearly above 6 db in quiet test conditions without added background noise, it rapidly declines when white noise fragments are presented, even when an earmuff is put in place. Results presented in the previous section Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 4

SNR (db) -15-10 -5 0 5 10 15 20 54 58 62 70HPD 77HPD 83HPD 90HPD quiet 1000 2000 3000 4000 5000 6000 7000 8000 Frequency F2 (Hz) FIGURE 2: Average DPOAE signal-to-noise ratio as a function of second stimulus frequency (F2) and background noise level (54 db(a) to 90 db(a)), HPD indicates that an earmuff has been placed on top of the OAE probe, quiet refers to the baseline condition where no white noise was added. The integrity cut-off values SNR 3 db and 6 db are indicated as well. reveal that this decrease in signal-to-noise ratio is not due to signal deterioration, expect for 83 db(a) and above. As a consequence, artifact detection based on a signal-to-noise ratio would incorrectly lead to rejections of the majority of the signals, not because the signals are too weak, but because the ambient noise is too high. Hence, for screening purpose, an alternative approach is introduced where amplitude variation is assessed rather than absolute levels. To address DPOAE signal variation, per subject the DPOAE signal in the baseline condition without added ambient noise is subtracted from the signal in the respective test conditions for corresponding frequencies. This way the influence of the particular measurement equipment on signal detection is canceled out. Per subject only those frequencies are retained with a signal-to-noise ratio of at least 3 db in the baseline condition, to avoid that potential artifacts (SNR below 3 db) are taken as a reference and hence by definition meaningless variation around this artifact would influence the statistical modeling. Based on the previous findings, results from the test conditions in 83 db(a) and 90 db(a) ambient white noise are discarded as well because signal estimation appears to be no longer accurate. Mixed-model linear regression is carried out with signal variation as outcome variable and subject as independent random factor. The candidate independent fixed factors are frequency, participant s age, gender, ear, use of earmuff and corrected ambient noise level. For this last variable the ambient background noise levels for test conditions with earmuff have been corrected with the interpolated assumed protection values given by the manufacturer (Table 1). Variables that significantly reduce the models deviance are retained (α = 0.1). The final model is summarized in Table 3 where only gender has a clearly significant influence (p < 0.05). Frequency is retained as well, but here the effect is less pronounced (0.05 < p < 0.1). Figure 3 illustrates that for male participant the DPOAE signals in noise conditions vary less compared to their DPOAE baseline, and variation slightly increases for higher frequencies. Apart from the signal variation, it should be noted that DPOAE signal amplitude as such is on average higher for female participants (7.73 db female, 6.70 db male) and for higher frequencies. Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 5

Variable Coeff p (Intercept) -1.555e+00 < 0.001 Frequency DPOAE 7.204e-05 0.08 Gender Male 1.016e+00 0.04 TABLE 3: Coefficients and corresponding p-value of the fixed independent factors included in the mixed-model regression model with DPOAE signal variation as outcome variable: DPOAE signal frequency and gender. Signal variation (db) -3-2 -1 0 1 2 3 Female Male 1000 2000 3000 4000 5000 Frequency OAE (Hz) FIGURE 3: DPOAE signal variation in elevated ambient background noise as a function of DPOAE frequency and gender: predictions (full line) with confidence interval (dashed line). Frequency-efficient screening To reduce measurement time (4 minutes per DPOAE measurement in the current setup) one could opt to focus on those frequency bands with the least interference from ambient background noise. This is of course related to the spectrum of the background noise, but as passive noise reduction (from the OAE probe alone or in combination with earmuff) increases with increasing frequency, higher DPOAE frequencies are in general less affected by external noise from the environment. From Figure 4a it can be seen that from 2.5 khz (corresponding to a primary F2 tone of 3910 Hz) the DPOAE noise level under hearing protector equals the noise level in quiet conditions for 70 db(a) ambient white noise and even for the most adverse condition shown (62 db(a) white noise without earmuff), DPOAE signal and noise are on average clearly distinguishable. Figure 4b has been added to illustrate that this decrease in DPOAE noise is not simply due to a decrease in ambient noise levels. In addition, Figure 4a also confirms the typical spectrum of DPOAE-measurement with two distinct peaks. As the second peak lies in the frequency range where the DPOAE noise is lowest, this is again an argument to focus screening DPOAE measurement on this higher frequency region. For the highest frequencies, the DPOAE signal rapidly declines, but they remain clearly distinguishable even for higher levels of ambient noise. Finally, per frequency oneway average measures intraclass correlation coefficient (ICC) is calculated to quantify the fraction of total variance accounted for by variance between test conditions. Observations for 83 db(a) and 90 db(a) ambient noise are again excluded. Because ICC magnitude is related to between-subject variability, the standard error of measurement (SEM) is calculated as well. These quantities are calculated per frequency, as frequencies with higher ICC and lower SEM are more eligible than others, especially when the test time is limited. Here, best results are found between 2.5 khz and 4.5 khz, which nicely fits in with the Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 6

Level (db) -10 0 5 10 15 20 25 54 58 62 70HPD 77HPD quiet Level (db) 20 40 60 80 54 58 62 70HPD 77HPD quiet 1 2 3 4 5 Frequency OAE (khz) (A) DPOAE noise (dashed line) and DPOAE signal (full line). 1 2 3 4 5 Frequency OAE (khz) (B) Ambient background noise. FIGURE 4: Level variation as a function of DPOAE response frequency for different test condition: ambient white noise from 54 db(a) to 77 db(a) and without extra white noise (quiet). Use of earmuff is indicated with HPD. above findings. However, it also puts a caveat for the reliability of frequencies above 4.5 khz. DISCUSSION This paper addresses the possibility and requirements for implementing DPOAE in-field as a screening tool for occupational hearing damage. Initially, only normal-hearing subjects are included to study the effects of suboptimal test conditions when healthy DPOAE signals are expected. Currently, a follow-up study with hearing impaired subjects is carried out. The present results reveal that DPOAE signals are relatively unaffected by ambient noise, especially when extra noise reduction is applied and bearing in mind that this research is done for screening, i.e. detecting variation in DPOAE signals that require follow-up, not for assessing a person s absolute DPOAE levels. Nevertheless, even with an earmuff placed on top of the OAE probe, DPOAE signal levels become unreliable in 83 db(a) white noise and higher. This could be due to the processing algorithms failing to detect signals in excessive background noise. It is also not unthinkable that DPOAE signals are actually reduced because of contralateral suppression, as this phenomena has been registered in lower levels of ambient noise then here included [10]. Finally, it is extremely unlikely that the ambient noise levels themselves have introduced temporary threshold shifts, taking into account the ambient noise levels, the short exposure time and noise reduction by the earmuff. For the other test condition, the relevant within-subject signal variation compared to the baseline DPOAE lies within the same order of magnitude as the minimal detectable difference calculated previously [3]. This variation is smaller for cases with initial lower baseline DPOAE signals, in casu male participants and lower stimulus frequencies. For signal levels closer to the DPOAE noise, this noise level becomes indeed relatively more important and thus limits observed signal variation. Although DPOAE signals and signal variation do not vary significantly with ambient noise, the overall signal variation between test conditions (including the baseline condition) is higher then in previous work [3]. There also a lower signal-to-noise ratio is associated with lower correlation between repeated measurements. In addition, OAE probe positioning might be less Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 7

ICC 0.88 0.92 0.96 SEM 1.0 1.2 1.4 1.6 1.8 2.0 1000 2000 3000 4000 5000 Frequency OAE (Hz) 1000 2000 3000 4000 5000 Frequency OAE (Hz) (A) ICC. (B) SEM. FIGURE 5: Stability of DPOAE signal across test conditions as a function of frequency: intraclass correlation coefficient (ICC) and standard error of measurement (SEM). stable in the current test setup because of earmuff placement. Finally, in accordance with previous work [6] these results confirm that focusing on a higher frequency range between 2.5 khz and 4.5 khz could be beneficial for accurate and efficient OAE screening. This region is also most sensitive for noise-induced hearing loss [11]. Currently, research applying DPOAE screening protocol for normal-hearing and hearing impaired subjects in industry is under construction. In future, large-scale implementation in real-working conditions would not only enable improved individual prevention of occupational noise-induced hearing loss, it would also allow to follow-up in more detail the relationship between momentaneous noise exposure and hearing damage over a longer time period. CONCLUSION This paper investigate how DPOAE registration can be made more suitable for in-field monitoring of early signs of noise-induced hearing damage. First, DPOAE signal estimation is made less dependent from ambient noise by setting alternative pass/refer criteria. DPOAE amplitude appears quite stable in white noise levels below 83 db(a) provided that extra noise reduction is applied, whereas higher ambient levels do affect measured DPOAE signal amplitude. Within the tolerable range of ambient noise, maximal allowable signal decrease compared to an individual s baseline DPOAE acquired in optimal test condition is estimated at 2 db. Further decrease requires intervention. Second, the efficiency of in-field DPOAE registration is increased by selecting frequency regions where DPOAE signals show least intra-subject variation and DPOAE noise levels are lowest, i.e. between 2.5 khz and 4.5 khz. This findings will be implemented in an in-situ protocol for hearing conservation, allowing to assess regularly on an individual scale whether in-place noise reduction measures are sufficient, or whether by contrast follow-up is needed. Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 8

ACKNOWLEDGMENTS Annelies Bockstael is postdoctoral fellow of the Research Foundation-Flanders (FWO); the support of this organization is gratefully acknowledged. REFERENCES [1] A. Bockstael, L. De Bruyne, B. Vinck, and D. Botteldooren, Hearing protection in industry: companies policy and workers perception, International Journal of Industrial Ergonomics (In press). [2] L. Marshall, L. JA, and L. Heller, Distortion-product otoacoustic emissions as a screening tool for noise-induced hearing loss, Noise and Health 3, 43 60 (2001). [3] H. Keppler, I. Dhooge, L. Maes, W. D haenens, A. Bockstael, B. Philips, F. Swinnen, and B. Vinck, Transient-evoked and distortion product otoacoustic emissions: A short-term test-retest reliability study, International Journal of Audiology 49, 99 109 (2010). [4] G. Popelka, R. Karzon, and R. Clary, Identification of noise sources that influence distortion product otoacoustic emission measurements in human neonates, Ear and hearing 19, 319 (1998). [5] V. Chan, E. Wong, and B. Mcpherson, Occupational hearing loss: screening with distortion-product otoacoustic emissions, International Journal of Audiology 43, 323 329 (2004). [6] A. Bockstael, D. Botteldooren, H. Keppler, L. Degraeve, and B. Vinck, Hearing protectors and the possibility to detect noise-induced hearing damage using otoacoustic emissions in situ, in Proceedings of InterNoise 2012 (New York) (2012). [7] V. Nadon, A. Bockstael, H. Keppler, J.-M. Lina, D. Botteldooren, and J. Voix, Field recording of dpoae in industrial noises: passive attenuation and adaptive noise reduction, in Proceedings of ICA 2013 (Submitted). [8] International Standard Organisation, Acoustics - Hearing protectors - Part 1: Subjective method for the measurement of sound attenuation (1990). [9] A. Bockstael, T. Van Renterghem, D. Botteldooren, W. D haenens, H. Keppler, L. Maes, F. Swinnen, B. Philips, and B. Vinck, Verifying the attenuation of earplugs in situ: method validation on human subjects including individualized numerical simulations, J. Acoust. Soc. Am. 125, 1479 1489 (2009). [10] H. Keppler, I. Dhooge, P. Corthals, L. Maes, W. D haenens, A. Bockstael, B. Philips, F. Swinnen, and B. Vinck, The effects of aging on evoked otoacoustic emissions and efferent suppression of transient evoked otoacoustic emissions, Clinical Neurophysiology 121, 359 365 (2010). [11] B. Prieve, M. Gorga, A. Schmidt, S. Neely, J. Peters, L. Schultes, and W. Jesteadt, Analysis of transient-evoked otoacoustic emissions in normal-hearing and hearing-impaired ears, J. Acoust. Soc. Am. 93, 3308 (1993). Proceedings of Meetings on Acoustics, Vol. 19, 040018 (2013) Page 9