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Transient Evoked Otoacoustic Emissions in Patients with Normal Hearing and in Patients with Hearing Loss
Abstract and Figures
1) To evaluate transient evoked otoacoustic emission (TEOAE) test performance when measurements are made under routine clinical conditions. 2) To evaluate TEOAE test performance as a function of frequency and as a function of the magnitude of hearing loss. 3) To compare test performance using univariate and multivariate approaches to data analyses. 4) To provide a means of interpreting clinical TEOAE measurements.
TEOAEs were measured in 452 ears of 246 patients. All measurements were made after acoustic immittance assessments, which were used to demonstrate that middle-ear function was normal at the time of the TEOAE test. TEOAE amplitudes and signal to noise ratios (SNRs), analyzed into octave bands centered at 1, 2, and 4 kHz, were compared with the pure-tone threshold at the same frequencies. Data were analyzed with clinical decision theory, cumulative distributions, discriminant analyses, and logistic regressions.
Using univariate analysis techniques, TEOAEs accurately identified auditory status at 2 and 4 kHz but were less accurate at 1 kHz. Test performance was best when audiometric thresholds between 20 and 30 dB HL were used as the criteria for normal hearing. TEOAE SNR resulted in better test performance than did TEOAE amplitude alone; this effect decreased as frequency increased. Multivariate analysis methods resulted in better separation between normal and impaired ears than did univariate approaches, which relied on only TEOAE amplitude or SNR when test frequency band and audiometric frequency were the same. This improvement in test performance was greatest at 1 kHz, decreased as frequency increased, and was negligible at 4 kHz.
TEOAEs can be used to identify hearing loss in children under routine clinical conditions. Univariate tests accurately identified auditory status at mid and high frequencies but performed more poorly at lower frequencies. The decrease in performance as frequency decreases may be a result of increased noise at lower frequencies but also may be due to properties of the measurement paradigm ("QuickScreen," high-pass filter at 0.8 kHz), which would not be ideal for recording energy around 1 kHz. The improvement in test performance when SNR was used and the interaction of this effect with frequency, however, would be consistent with the view that test performance in lower frequencies is at least partially influenced by the level of background noise. Multivariate analysis techniques improved test performance compared with the more traditional univariate approaches to data analysis. An approach is provided that allows one to assign measured TEOAE amplitudes, SNRs, or outputs from multivariate analyses to one of three categories: response properties consistent with normal hearing; results consistent with hearing loss; hearing status undetermined.
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... We also note that the SNRs for the OAEs detected by our system are smaller at the lower frequencies. This is in line with existing literature [33] which confirms that transient-evoked OAEs are better at mid-range frequencies than the lower frequencies. ...
We present the first wireless earbud hardware that can perform hearing screening by detecting otoacoustic emissions. The conventional wisdom has been that detecting otoacoustic emissions, which are the faint sounds generated by the cochlea, requires sensitive and expensive acoustic hardware. Thus, medical devices for hearing screening cost thousands of dollars and are inaccessible in low and middle income countries. We show that by designing wireless earbuds using low-cost acoustic hardware and combining them with wireless sensing algorithms, we can reliably identify otoacoustic emissions and perform hearing screening. Our algorithms combine frequency modulated chirps with wideband pulses emitted from a low-cost speaker to reliably separate otoacoustic emissions from in-ear reflections and echoes. We conducted a clinical study with 50 ears across two healthcare sites. Our study shows that the low-cost earbuds detect hearing loss with 100% sensitivity and 89.7% specificity, which is comparable to the performance of a $8000 medical device. By developing low-cost and open-source wearable technology, our work may help address global health inequities in hearing screening by democratizing these medical devices.
... It was reasoned that the larger area values indicate robust DPs, and the smaller values indicate diminished DPs, thereby measuring the overall strength of the cochlear amplifier in their respective frequency bands (Gates et al. 2002). We utilized DPOAE SNR values because they might be more sensitive than amplitude values to differentiate impaired and normal ears (Hussain et al. 1998), and recent evidence suggests that physiological noise might influence suprathreshold speech perception (Stiepan et al. 2020). ...
Objectives:
About 15% of U.S. adults report speech perception difficulties despite showing normal audiograms. Recent research suggests that genetic factors might influence the phenotypic spectrum of speech perception difficulties. The primary objective of the present study was to describe a conceptual framework of a deep phenotyping method, referred to as AudioChipping, for deconstructing and quantifying complex audiometric phenotypes.
Design:
In a sample of 70 females 18 to 35 years of age with normal audiograms (from 250 to 8000 Hz), the study measured behavioral hearing thresholds (250 to 16,000 Hz), distortion product otoacoustic emissions (1000 to 16,000 Hz), click-evoked auditory brainstem responses (ABR), complex ABR (cABR), QuickSIN, dichotic digit test score, loudness discomfort level, and noise exposure background. The speech perception difficulties were evaluated using the Speech, Spatial, and Quality of Hearing Scale-12-item version (SSQ). A multiple linear regression model was used to determine the relationship between SSQ scores and audiometric measures. Participants were categorized into three groups (i.e., high, mid, and low) using the SSQ scores before performing the clustering analysis. Audiometric measures were normalized and standardized before performing unsupervised k-means clustering to generate AudioChip.
Results:
The results showed that SSQ and noise exposure background exhibited a significant negative correlation. ABR wave I amplitude, cABR offset latency, cABR response morphology, and loudness discomfort level were significant predictors for SSQ scores. These predictors explained about 18% of the variance in the SSQ score. The k-means clustering was used to split the participants into three major groups; one of these clusters revealed 53% of participants with low SSQ.
Conclusions:
Our study highlighted the relationship between SSQ and auditory coding precision in the auditory brainstem in normal-hearing young females. AudioChip was useful in delineating and quantifying internal homogeneity and heterogeneity in audiometric measures among individuals with a range of SSQ scores. AudioChip could help identify the genotype-phenotype relationship, document longitudinal changes in auditory phenotypes, and pair individuals in case-control groups for the genetic association analysis.
... It is technically not a test of hearing, but rather a reflection of inner ear (Gorga et al., 1997;Hussain et al., 1998). Both, TEOAEs and DPOAEs have been used to screen for hearing loss in infants and children. ...
Abstract
Cochlear microphonic (CM) is one of the main components observed in ECochG. It is a stimulus-related potential generated by both inner and outer hair cells. Post-auricular muscle reflex (PAMR) is a large sound evoked myogenic compound action potentials that could be recorded over the post auricular muscle located behind the pinna. Objectives: This study aimed to study the effect of mild to moderate conductive or sensorineural hearing loss on CM and PAMR. Subjects and method: Control group consisted of 22 normal children who had bilateral normal peripheral hearing. Study group consisted of 45 children with hearing loss. They were subdivided into three subgroups; SGa included 15 children with mild to moderate conductive hearing loss, SGb included 15 children with mild to moderate sensorineural hearing loss, SGc of 15 patients with auditory neuropathy with different degrees of hearing loss. All subjects in the studied groups are submitted to basic audiologiacl evaluation, (CM) and (PAMR). Results: CM was recorded in all studied groups. There was no statistically significant difference in CM latency and amplitude between normal hearing (CG) and SNHL (SGb) or AN children (SGc). However, in conductive hearing loss (SGa), latency of CM was significantly prolonged than all other groups. PAMR was identified in almost normal hearing children (CG), children with CHL or SNHL (SGa and SGb). In auditory neuropathy children (SGc), PAMR was recorded in only 13.3%. There were no statistically significant difference between all studied groups as regard their latency and amplitude. Hearing threshold estimated by measuring the difference between mean threshold at 2-4 kHz and PAMR thresholds to be 10 dBSL in normal children, 11.1 dBSL in children with mild to moderate conductive hearing loss and 10.1 dBSL in children with mild to moderate SNHL. Conclusion: CM can be used as a method for detecting OHCs function even with ME affection. PAMR can be used as an objective test for threshold detection in normal children and children with hearing loss but not in AN. Keywords: Cochlear Microphonic (CM) and Post Auricular Muscle Reflex (PAMR).
Objectives
This study aims to develop deep learning (DL) models for the quantitative prediction of hearing thresholds based on stimulus-frequency otoacoustic emissions (SFOAEs) evoked by swept tones.
Design
A total of 174 ears with normal hearing and 388 ears with sensorineural hearing loss were studied. SFOAEs in the 0.3 to 4.3 kHz frequency range were recorded using linearly swept tones at a rate of 2 Hz/msec, with stimulus level changing from 40 to 60 dB SPL in 10 dB steps. Four DL models were used to predict hearing thresholds at octave frequencies from 0.5 to 4 kHz. The models—a conventional convolutional neural network (CNN), a hybrid CNN-k-nearest neighbor (KNN), a hybrid CNN-support vector machine (SVM), and a hybrid CNN-random forest (RF)—were individually built for each frequency. The input to the DL models was the measured raw SFOAE amplitude spectra and their corresponding signal to noise ratio spectra. All DL models shared a CNN-based feature self-extractor. They differed in that the conventional CNN utilized a fully connected layer to make the final regression decision, whereas the hybrid CNN-KNN, CNN-SVM, and CNN-RF models were designed by replacing the last fully connected layer of CNN model with a traditional machine learning (ML) regressor, that is, KNN, SVM, and RF, respectively. The model performance was evaluated using mean absolute error and SE averaged over 20 repetitions of 5 × 5 fold nested cross-validation. The performance of the proposed DL models was compared with two types of traditional ML models.
Results
The proposed SFOAE-based DL models resulted in an optimal mean absolute error of 5.98, 5.22, 5.51, and 6.06 dB at 0.5, 1, 2, and 4 kHz, respectively, superior to that obtained by the traditional ML models. The produced SEs were 8.55, 7.27, 7.58, and 7.95 dB at 0.5, 1, 2, and 4 kHz, respectively. All the DL models outperformed any of the traditional ML models.
Conclusions
The proposed swept-tone SFOAE-based DL models were capable of quantitatively predicting hearing thresholds with satisfactory performance. With DL techniques, the underlying relationship between SFOAEs and hearing thresholds at disparate frequencies was explored and captured, potentially improving the diagnostic value of SFOAEs.
Although averaging is effective in reducing noise, its efficiency rapidly decreases beyond several hundred averages. Depending on environmental and patient noise levels, several hundred averages may be insufficient for informed clinical decision making. The predictable nature of the otoacoustic emission (OAE) and noise during time-synchronous averaging implicates the use of predictive modeling as an alternative to increased averaging when noise is high. Click-evoked OAEs were measured in 98, normal-hearing subjects. Average OAE and noise levels were calculated for subsets of the total number of averages and then fit using variants of a power function. The accuracy of the models was quantified as the difference between the measured value and model output. Models were used to predict the OAE signal-to-noise ratio (SNR) for a criterion noise level. Based on predictions, the OAE was categorized as present or absent. Model-based decisions were compared to decisions from direct measurements. Model accuracy improved as the number of averages (and SNR in the case of OAEs) from which the model was derived increased. Model-based classifications permitted correct categorization of the OAE status from fewer averages than measurement-based classifications. Furthermore, model-based predictions resulted in fewer false positives (i.e., absent OAE despite normal hearing).
Purpose
In clinical practice, otoacoustic emissions (OAEs) are interpreted as either “present” or “absent.” However, OAEs have the potential to inform about etiology and severity of hearing loss if analyzed in other dimensions. A proposed method uses the nonlinear component of the distortion product OAEs together with stimulus frequency OAEs to construct a joint reflection–distortion profile. The objective of the current study is to determine if joint reflection–distortion profiles can be created using long-latency (LL) components of transient evoked OAEs (TEOAEs) as the reflection-type emission.
Method
LL TEOAEs and the nonlinear distortion OAEs were measured from adult ears. Individual input–output (I/O) functions were created, and OAE level was normalized by dividing by the stimulus level yielding individual gain functions. Peak strength, compression threshold, and OAE level at compression threshold were derived from individual gain functions to create joint reflection–distortion profiles.
Results
TEOAEs with a poststimulus window starting at 6 ms had I/O functions with compression characteristics similar to LL TEOAE components. The model fit the LL gain functions, which had R ² > .93, significantly better than the nonlinear distortion OAE gain functions, which had R ² = .596–.99. Interquartile ranges for joint reflection–distortion profiles were larger for compression threshold and OAE level at compression threshold but smaller for peak strength than those previously published.
Conclusions
The gain function fits LL TEOAEs well. Joint reflection–distortion profiles are a promising method that could enhance diagnosis of hearing loss, and use of the LL TEOAE in the profile for peak strength may be important because of narrow interquartile ranges.
Supplemental Material
https://doi.org/10.23641/asha.20323593
Contralateral noise inhibits the amplitudes of cochlear and neural responses. These measures may hold potential diagnostic utility. The medial olivocochlear (MOC) reflex underlies the inhibition of cochlear responses but the extent to which it contributes to inhibition of neural responses remains unclear. Mertes and Leek [J. Acoust. Soc. Am. 140, 2027–2038 (2016)] recently examined contralateral inhibition of cochlear responses [transient-evoked otoacoustic emissions (TEOAEs)] and neural responses [auditory steady-state responses (ASSRs)] in humans and found that the two measures were not correlated, but potential confounds of older age and hearing loss were present. The current study controlled for these confounds by examining a group of young, normal-hearing adults. Additionally, measurements of the auditory brainstem response (ABR) were obtained. Responses were elicited using clicks with and without contralateral broadband noise. Changes in TEOAE and ASSR magnitude as well as ABR wave V latency were examined. Results indicated that contralateral inhibition of ASSRs was significantly larger than that of TEOAEs and that the two measures were uncorrelated. Additionally, there was no significant change in wave V latency. Results suggest that further work is needed to understand the mechanism underlying contralateral inhibition of the ASSR.
The long-term outcomes of newborns exposed to SARS-CoV-2 infection in utero or during the first hours of life are still unknown. We performed a single-center, prospective, observational study of newborns born from mothers with microbiologically confirmed SARS-CoV-2 infection in pregnancy or at time of delivery. Infants were offered a multidisciplinary follow-up consisting of nasopharyngeal Polymerase Chain Reaction test at birth and at 48–72 h of life, auxological growth and neurological development, serologic testing, and audiological and ophthalmological assessments. One-hundred ninety-eight mothers and 199 newborns were enrolled. Of the 199 newborns, 171 underwent nasopharyngeal swab, four (2.3%) and two (1.15%) children tested positive at birth and 48–72 h of life, respectively. None had SARS-CoV-2 related symptoms. Auxologic and neurologic development were normal in all children during follow-up. Nine out of 59 infants had SARS-CoV-2 IgG at 3 months of life, which was associated with a positive nasopharyngeal swab at birth (P = 0.04). Twenty seven out of 143 (18.8%) newborns had pathologic transitory evoked otoacoustic emissions at birth, although 14/27 repeated after 1 month were normal. Audiological evaluation was completed with Auditory Brainstem Response between the third and sixth month of life in 34 children, showing in all normal hearing threshold. The ophthalmological evaluation found retinal vascular anomalies in 3/20 (15%) children, immature visual acuity in 5/20 (25%) children, and reduced distance attention in 6/20 cases (30%).
Conclusions: Our study showed that the neonatal and mid-term multidisciplinary outcomes of newborns exposed to SARS-CoV-2 infection in utero or during the first hours of life are mostly positive, with the exception of ophthalmologic findings which, in a preliminary cohort, were abnormal in about 15% of cases. Further prospective, longitudinal studies are needed to better understand the clinical outcomes of children exposed to SARS-CoV-2 in utero and in the early postnatal life. What is Known:
• In utero mother-to-child transmission of SARS-CoV-2 has been documented by several independent studies.
• Neonatal COVID-19 is a systemic disease that can be severe, although rarely.
What is New:
• Newborns exposed in utero to SARS-CoV-2 have mostly a normal auxological, audiological, and neurological development during the first months of life.
• Fundus fluorescein angiography revealed that up to 5% of newborns exposed in utero to SARS-CoV2 can show retinal and choroidal abnormalities, including peripheral hypofluorescence of the choroid and increased vascular tortuosity.
In this work, we study the effect of different stimulation levels on TEOAEs in the hearing process using non-linear models for the stimulus levels (10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, and 120) dB. We found that the latency as a function to stimulation level, by the results of TEOAEs we get from the different stimulus levels in the relationship of time-frequency. Therefore, relationship of time-frequency is very important in comparison results the different stimulus level with the previous studies and also useful in the study of hearing process in humans. At the analysis of relationship of time-frequency we get a lot of the results that show the characteristics for TEOAEs. From these results obtained in study the effect of different stimulus levels for TEOAEs in the relationship of time-frequency are the energy distribution and waveform behavior of TEOAEs. Energy distribution of TEOAEs shows the pool (concentration) energy in a number of spots (points) and the energy distribution varies from one stimulus level to another. Effect of waveform behavior TEOAEs by different stimulus levels, so latency is as a function to the frequency and the stimulation level.
Objectives:
Serological biomarkers, common to many areas of medicine, have the potential to inform on the health of the human body and to give early warning of risk of compromised function or illness before symptoms are experienced. Serological measurement of prestin, a motor protein uniquely produced and expressed in outer hair cells, has recently been identified as a potential biomarker to inform on the health of the cochlea. Before any test can be introduced into the clinical toolkit, the reproducibility of the measurement when repeated in the same subject must be considered. The primary objective of this study is to outline the test-retest reliability estimates and normative ranges for serological prestin in healthy young adults with normal hearing. In addition, we examine the relation between serum prestin levels and otoacoustic emissions (OAEs) to compare this OHC-specific protein to the most common measure of OHC function currently used in hearing assessments.
Design:
We measured prestin levels serologically from circulating blood in 34 young adults (18 to 24 years old) with clinically normal pure-tone audiometric averages at five different timepoints up to six months apart (average intervals between measurements ranged from <1 week to 7 weeks apart). To guide future studies of clinical populations, we present the standard error of the measurement, reference normative values, and multiple measures of reliability. Additionally, we measured transient evoked OAEs at the same five timepoints and used correlation coefficients to examine the relation between OAEs and prestin levels (pg/mL).
Results:
Serum prestin levels demonstrated good to excellent reliability between and across the five different time points, with correlation coefficients and intraclass correlations >0.8. Across sessions, the average serum prestin level was 250.20 pg/mL, with a standard error of measurement of 7.28 pg/mL. Moreover, positive correlations (generally weak to moderate) were found between prestin levels and OAE magnitudes and signal-to-noise ratios.
Conclusions:
Findings characterize serum prestin in healthy young adults with normal hearing and provide initial normative data that may be critical to interpreting results from individuals with sensorineural hearing loss. Our results demonstrate reliability of serum prestin levels in a sample of normal-hearing young adults across five test sessions up to 6 months apart, paving the way for testing larger samples to more accurately estimate test-retest standards for clinical protocols, including those involving serial monitoring. The positive correlations between serum prestin and OAE levels, although weak to moderate, reinforce that the source of serum prestin is likely the outer hair cells in the inner ear, but also that serum prestin and OAEs each may also index aspects of biologic function not common to the other.
Otoacoustic emissions are cochlea-generated low intensity sounds detectable in the external auditory meatus either spontaneously or in response to particular acoustic stimuli. Current research into otoacoustic emissions is briefly reviewed, with particular reference to their clinical applications. This study compares the pure tone audiograms and 'distortion product' otoacoustic emissions of 50 ears (25 normal, 25 with sensorineural hearing deficits). The standard pure tone audiogram thresholds have been compared with the distortion product results and a statistically significant association found.
Transient‐evoked otoacoustic emissions (TEOAEs) were measured in 113 normal‐hearing and hearing‐impaired ears to examine repeatability within a test session, which TEOAE parameter (level, TEOAE level‐to‐noise or reproducibility) best identified hearing loss and if the TEOAE separated into frequency‐specific bands identified hearing loss in a corresponding frequency region. TEOAEs and stimulus levels were found to be very repeatable. For broadband TEOAEs, TEOAE level, TEOAE‐to‐noise, and % reproducibility were found to identify hearing loss equally well, based on measurement of the area underlying relative operator characteristic curves. Analysis for frequency‐specific bands showed that separation of normal‐hearing and hearing‐impaired ears depended on frequency, with best identification at 2000 and 4000 Hz, identification at 1000 Hz slightly worse, and virtually no separation between normal‐hearing and hearing‐impaired ears at 500 Hz. Again, all three parameters were essentially equal in identifying hearing loss. Subjective evaluations of presence or absence of TEOAEs was highly correlated between two judges, with good agreement for TEOAEs at 1000, 2000, and 4000 Hz. The findings from this study suggest that TEOAEs will be valuable for clinical use because of their repeatability and identification of hearing‐impaired ears.
Cochlear and neural auditory function for a series of 30 patients with acoustic neuroma was assessed pre- and postoperatively by transiently evoked otoacoustic emission (TEOAE), auditory brain stem response (ABR), and acoustic reflex measures. Employing a retrosigmoid surgical approach, physical integrity of the acoustic nerve was preserved for 22 patients. TEOAEs were observed preoperatively for 13 patients and postoperatively for 6 of them. Postoperative neural function remained unchanged or improved following surgery for 7 patients, and cochlear function decreased. TEOAE, ABR, and acoustic reflex measurements were considered valuable in providing information about site of lesion and probable mechanisms of injury associated with tumor removal.
colon; Otoacoustic emissions provide a useful measure of peripheral auditory processing. This report reviews emission findings for both normally hearing and hearing-impaired adults. Some additional information is presented about the effects of aging on emissions. Finally, a review of the test parameters that permit the optimal evaluation of emissions is presented.
(C) 1994, The American Journal of Otology, Inc.
Receiver operating characteristic graphs are shown to be a variant form of ordinal dominance graphs. The area above the latter graph and the area below the former graph are useful measures of both the size or importance of a difference between two populations and/or the accuracy of discrimination performance. The usual estimator for this area is closely related to the Mann-Whitney U statistic. Statistical literature on this area estimator is reviewed. For large sample sizes, the area estimator is approximately normally distributed. Formulas for the variance and the maximum variance of the area estimator are given. Several different methods of constructing confidence intervals for the area measure are presented and the strengths and weaknesses of each of these methods are discussed. Finally, the Appendix presents the derivation of a new mathematical result, the maximum variance of the area estimator over convex ordinal dominance graphs.
A new auditory phenomenon has been identified in the acoustic impulse response of the human ear. Using a signal averaging technique, a study has been made of the response of the closed external acoustic meatus to acoustic impulses near to the threshold of audibility. Particular attention has been paid to the waveform of the response at post excitation times in excess of 5 ms. No previous worker appears to have extended observations into this region. The response observed after about 5 ms is not a simple extension of the initial response attributable to the middle ear. The oscillatory response decay time constant was found to change from approximately 1 ms to over 12 ms at about this time. The slowly decaying response component was present in all normal ears tested, but was not present in ears with cochlear deafness. This component of the response appears to have its origin in some nonlinear mechanism probably located in the cochlea, responding mechanically to auditory stimulation, and dependent upon the normal functioning of the cochlea transduction process. A cochlear reflection hypothesis received some support from these results.