Characterizing spontaneous otoacoustic emissions across the human lifespan

Abstract

This study characterizes 1571 archival and newly acquired spontaneous otoacoustic emissions (SOAEs) from 632 human subjects with ages ranging from premature birth through the seventh decade of life. Automated detection and Lorentzian modeling were applied to identify SOAEs and characterize SOAE features throughout the human lifespan. Results confirm higher-level, higher-frequency, and more numerous SOAEs from neonates compared to young adults. Approximately 85% of newborns have measurable SOAEs as compared to 51%-68% for young adults. Newborn SOAEs are also an average of 5 to 6 dB higher in level than those from young-adult ears. These age differences may reflect immature ear-canal acoustics and/or the pristine condition of the neonatal cochlea. In addition, newborns as a group showed broader SOAE bandwidth and increased frequency jitter, possibly due to higher intracochlear noise; additionally, 22% of newborn SOAEs had a different, non-Lorentzian spectral shape. Aging effects were also observed: 40% of elderly ears had SOAEs, and these were greatly reduced in level, likely due to lower power gain in the aging cochlea. For all ages, SOAE bandwidths decreased with frequency in a way that mirrors the frequency dependence of stimulus-frequency otoacoustic emission delays as predicted by the standing-wave model of SOAE generation.

FIG. 1.

The mean noise baseline achieved after data cleaning in each of four age groups from the New Group. System noise (measured by inserting the probe in a Bruel and Kjaer 4157 ear simulator and averaging in the absence of stimuli) is shown for comparison. The adult groups track the system noise within a few dB over the entire frequency range. The newborns show noise elevated by 5–10 dB below 2 kHz, but adult-like noise levels above this frequency.

FIG. 2.

Example spectra and SOAEs from newborns in the Archival group. The inset shows the spectrum from a premature newborn with the highest level SOAE we have recorded, 36 dB SPL. No other age group showed SOAEs of this magnitude. In general, these exemplars illustrate the SOAE trends in the Archival data set, i.e., more numerous and higher level SOAEs in newborns than adults.

FIG. 3.

(Color online) Panels (A) and (B) show histograms of SOAE frequency and level for the Archival Group. Counts are shown as a percentage of the total number of SOAEs in each age group because of the varying numbers of subjects in each. Panel (C) shows a scatterplot of every SOAE in the Archival Group plotted as level vs frequency. Most notable is the higher level SOAEs from newborns.

FIG. 4.

Example SOAE spectra from individual ears representing each of the seven age categories in the New Group: newborns (premature and term), 6-month-old infants, teens (13–17 yr), young adults (18–25 yr), middle-aged adults (40–58 yr), and elderly adults (59–78 yr). The thick gray line in each panel is the median noise baseline value and the thin black line above the noise denotes the 5 SD boundary for this particular ear. Peaks marked with a circle were identified as true SOAEs; peaks marked with an x are those with insufficient SNR; unmarked peaks are too narrow to meet the nine-consecutive-points criterion. Also shown is an inset of an atypical elderly subject with many more SOAEs (>2 SD from the mean) than typical for that group.

FIG. 5.

(Color online) Panels (A) and (B) show histograms of SOAE frequency and level for the New Group. Counts are shown as a percentage of the total number of SOAEs in each age group because of the varying numbers of subjects in each. Panel (C) shows a scatterplot of every SOAE in the New Group plotted as level vs frequency. The newborns show the largest percentage of SOAEs at high frequencies and also the highest-level SOAEs in any age group.

FIG. 6.

(Color online) Six SOAEs from one young-adult ear and their Lorentzian model best fits. Parameters for each fit are given. Note that the goodness-of-fit as shown by the RMS residual did not depend heavily on SOAE level or frequency in these examples although in general, the model underestimated the BW of higher-level SOAEs. Generally, when the SOAE level was high, the bandwidth (BW/f₀) was narrow. Also, note that the lower the noise floor, the smaller the required standard deviation to consider an SOAE present.

FIG. 7.

(Color online) Four newborn SOAEs and their Lorentzian model best fits. Comparisons between adult fits in Fig. 6 and newborn fits here show that the Lorentzian model sometimes fails to capture the shape of the newborn SOAE. Mismatches are especially evident in the skirt region and in the underestimation of emission bandwidth near the peak. Model RMS residuals exceeded 2 dB in 22% of newborns but in only 3.5% of young-adult Lorentzian-model fits.

FIG. 8.

(Color online) Scatterplot showing values of the ratio $\hspace{0.17em}\text{BW}/{\text{BW}}_{\text{LE}}$ vs SOAE level. Age groups are identified by symbols. A loess trend line to the pooled data is shown to guide the eye. Close to one for the majority of SOAEs at low and moderate levels, the ratio decreases at higher levels, indicating that the Lorentzian model systematically underestimates the bandwidths of high-level SOAEs.

FIG. 9.

(Color online) Scatterplot showing SOAE fractional bandwidths ${\text{BW}}_{\text{LE}}/f_0$ vs SOAE level. Age groups are identified by symbols. Loess trend lines and 95% confidence intervals for each group are shown for age comparisons. SOAE bandwidths in newborns are significantly broader than bandwidths from the other two age groups.

FIG. 10.

Two example histograms used to determine SOAE jitter bandwidth ${\text{BW}}_{\text{JIT}}$. The histograms summarize the results of spectral analysis performed on each of the 180 1-s segments of the 3-min ear-canal recording. Counts give the number of times each frequency bin along the abscissa locates the Fourier coefficient of maximal amplitude about the nominal SOAE frequency. Counts do not necessarily sum to 180 because a 5 SD criterion was applied to the spectral peak of each 1-s segment in order to reduce noise. The jitter bandwidth ${\text{BW}}_{\text{JIT}}\hspace{0.17em}$ is the interquartile range (IQR) of the histogram. The histograms shown here are from adult SOAEs.

FIG. 11.

(Color online) Scatterplot of ${\text{BW}}_{\text{LE}}/f_0$ vs ${\text{BW}}_{\text{JIT}}/f_0$ showing the relationship between the Lorentzian-equivalent and jitter bandwidths. Age groups are identified by symbols. Loess trend lines for each age group are superposed on the data. A line of unit slope (dashed line) approximates the relationship over most of the range.

FIG. 12.

(Color online) Scatterplot of values N_SOAE vs SOAE frequency. N_SOAE is defined as $\sqrt{f_{\mathrm{b}}{f}_{\mathrm{a}}}/(f_{\mathrm{b}}-f_{\mathrm{a}})$ and represents the inverse fractional spacing between adjacent SOAEs. Age groups are identified by symbols. The solid line represents the power-law approximation (13.7(f/[kHz])^0.31) to the peak of the distribution (characteristic minimum spacings) reproduced from Fig. 3 of Shera (2003).

FIG. 13.

(Color online) Scatterplot of values N_BW vs SOAE frequency. N_BW is defined as $f/{\text{BW}}_{\text{LE}}$ and represents the inverse fractional SOAE bandwidth. Age groups are identified by symbols. Solid lines show power-law fits to the individual group data (parameters given in the text). The dotted line shows the power-law approximation N_SFOAE = 11.1(f/[kHz])^0.37 to high-frequency SFOAE delay (in periods) reproduced from Fig. 3 of Shera (2003).