Thesis (M. Communication Pathology)--University of Pretoria, 2004. / Includes bibliographical references.

M.Ing. (Electrical and Electronic Engineering) / This dissertation presents a comprehensive electrical model of the human auditory periphery. The model focuses on the generation and transmission of otoacoustic emissions (OAEs) under biometric conditions. The auditory system model was divided and studied in three sections, namely the outer, middle and inner ear sections. Existing models were used and improved for the study. The outer ear model was derived using electroacoustic analogies. The middle ear model was derived empirically. The inner ear model was derived by relating the mechanical properties of the inner ear to electrical principles. The outer ear model includes an analog diffraction circuit and a linear transmission line representation of the auditory canal and the concha. The variation of the radius of the auditory canal along its length was incorporated when computing the model of the outer ear. A pair of second order polynomials were used to create a new radius-length function which approximates the relationship between the radius of the auditory canal and its length. The frequency response of the outer ear model obtained using the radius-length function gave a wide frequency range representation of the outer ear characteristics. The middle ear is modelled using an analog network. Only the linear operation region of the middle ear was considered, thus excluding its reflex nonlinear mechanisms, namely; the stapedius muscle action and the stapes clipping displacement. The influence of the middle ear on the transmission of OAEs was evaluated by considering both the forward and reverse transmission characteristics/path of the middle ear. The middle ear response demonstrated great sensitivity to changes in the terminal loads connected to the middle ear as well as the transformer ratio. The inner ear behavior is represented by means of a nonlinear transmission line model. The nonlinear mechanism of the outer hair cells, which are taken as the primary sources of OAEs, are modelled using nonlinear voltage sources. The inner ear model was evaluated for conditions of both the active and inactive outer hair cells voltage sources. Due to limitations in the simulation software, a reduced active inner ear model was computed.The influence of the number of segments of the inner ear was explored. A reduced inner ear model having 40 segments was found to be sufficient in representing the frequency characteristics of the inner ear, whilst preserving the frequency-latency relationship of OAEs. The study not only improved the model of the auditory periphery, but also suggested several factors that can be incorporated in future research in order to better design signal acquisition and processing methods for OAE biometric applications.

Background: Multidrug-resistant tuberculosis (MDR-TB) patients receive aminoglycosides as part of their treatment. These drugs are ototoxic, and can cause permanent damage to the cochlea, resulting in a debilitating hearing loss, which has a negative impact on an individual's quality of life. Early detection and management of an ototoxic hearing loss can minimise the impact of the hearing loss on the person's social, emotional, and vocational wellbeing. While patients with MDR-TB are often very ill, it might be ideal to use an objective test that does not require active participation from the patient. In this way, the reliability and validity of the test will not be affected by the patient's state. Distortion product otoacoustic emissions (DPOAEs) at 2f1-f2 are a viable option, as it evaluates cochlear function, specifically the outer hair cells, which are affected first by ototoxic medication. Method: This thesis used a sequential study design aimed to determine the DPOAE stimulus parameters that yield (a) the highest level and the most reliable, sensitive and specific DPOAEs reported in the literature, (b) the highest level and the most reliable DPOAEs in healthy, normally hearing adults, and (c) the most sensitive and specific DPOAEs in participants with MDR-TB patients receiving ototoxic medication. High frequency pure tone audiometry (defined in this thesis as frequencies > 8 kHz) was used as the gold standard. Descriptive statistics, the intraclass correlation coefficient, Pearson's correlation coefficient and mixed model analyses were used to analyse the data. Results: Systematic review: The results of the systematic review indicated an L1/L2 setting of 75/75 dB SPL and f2/f1 value from 1.20 to 1.22 yielded the highest level DPOAEs. The systematic review results for stimulus parameters that yielded the highest test-retest reliability, sensitivity and specificity were inconclusive. Preliminary study with healthy normal hearing participants: The results of the preliminary study in healthy, normal-hearing participants indicated that the highest levels of DPOAEs were elicited with L1/L2 intensity levels of 65/65 and 65/55 dB SPL, and f2/f1 ratios of 1.18, 1.20 and 1.22, as determined by mixed model analyses (p < 0.05). These same stimulus parameters yielded the most reliable DPOAEs in both ears, as determined by intraclass correlation coefficient analysis. Main study with healthy, normal-hearing participants: Descriptive statistics and mixed model analysis showed stimulus intensity levels L1/L2 of 65/55 dB SPL, and f2/f1 ratios of 1.18 and 1.20, elicited the largest DPOAEs. The ratio of 1.20 yielded the largest DPOAEs < 5000 Hz and f2/f1 ratio of 1.18 the largest DPOAEs ≥ 5000 Hz. The second highest DPOAE levels were elicit by L1/L2 = 65/65 dB SPL and f2/f1 = 1.18. The test-retest reliability in this sample was not influenced by changing the stimulus parameters, and DPOAEs were only unreliable at an f2 frequency of 8 000 Hz. Study in participants with MDR-TB: Results in participants with MDR-TB receiving ototoxic medication indicated that the highest levels of DPOAEs were elicited with L1/L2 = 65/55 and an f2/f1 ratio of 1.18 at f2 ≥ 5000 Hz, followed by 65/65 and 1.18. For f2 < 5000 Hz, stimulus intensities of L1/L2 = 65/55 and an f2/f1 ratio of 1.20 yielded the largest DPOAE levels. Relating to sensitivity and specificity, the stimulus parameter combination of 65/55 dB and 1.18 detected the highest number of ears with outer hair cell damage in participants with MDR-TB receiving ototoxic medication. Conclusion: It should be considered to use an f2/f1 ratio of 1.18 for f2 ≥ 5000 Hz and 1.20 for f2 < 5000 Hz when monitoring for ototoxicity, to assist with early identification of outer hair cell damage, in conjunction with high frequency pure tone audiometry. This finding needs to be confirmed in a larger sample of participants with MDR-TB receiving ototoxic medication.

published_or_final_version / Speech and Hearing Sciences / Master / Master of Science in Audiology

Yao Jun. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

by Ma Wing-Kin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 121-124). / Chapter 1 --- Introduction to Otoacoustic Emissions --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Clinical Significance of the OAEs --- p.2 / Chapter 1.3 --- Classes of OAEs --- p.3 / Chapter 1.4 --- The Distortion Product OAEs --- p.4 / Chapter 1.4.1 --- Measurement of DPOAEs --- p.5 / Chapter 1.4.2 --- Some Properties of DPOAEs --- p.8 / Chapter 1.4.3 --- Noise Reduction of DPOAEs --- p.8 / Chapter 1.5 --- Goal of this work and Organization of the Thesis --- p.9 / Chapter 2 --- Review to some Topics in Narrowband Signal Estimation --- p.11 / Chapter 2.1 --- Fourier Transforms --- p.12 / Chapter 2.2 --- Periodogram ´ؤ Classical Spectrum Estimation Method --- p.15 / Chapter 2.2.1 --- Signal-to-Noise Ratios and Equivalent Noise Bandwidth --- p.17 / Chapter 2.2.2 --- Scalloping --- p.18 / Chapter 2.3 --- Maximum Likelihood Estimation --- p.19 / Chapter 2.3.1 --- Finding of the ML Estimator --- p.19 / Chapter 2.3.2 --- Properties of the ML Estimator --- p.21 / Chapter 3 --- Review to Adaptive Notch/Bandpass Filter --- p.23 / Chapter 3.1 --- Introduction --- p.23 / Chapter 3.2 --- Filter Structure --- p.24 / Chapter 3.3 --- Adaptation Algorithms --- p.25 / Chapter 3.3.1 --- Least Squares Method --- p.25 / Chapter 3.3.2 --- Least-Mean-Squares Algorithm --- p.27 / Chapter 3.3.3 --- Recursive-Least-Squares Algorithm --- p.28 / Chapter 3.4 --- LMS ANBF Versus RLS ANBF --- p.31 / Chapter 3.5 --- the IIR filter Versus ANBF --- p.31 / Chapter 4 --- Fast RLS Adaptive Notch/Bandpass Filter --- p.33 / Chapter 4.1 --- Motivation --- p.33 / Chapter 4.2 --- Theoretical Analysis of Sample Autocorrelation Matrix --- p.34 / Chapter 4.2.1 --- Solution of Φ (n) --- p.34 / Chapter 4.2.2 --- Approximation of Φ (n) --- p.35 / Chapter 4.3 --- Fast RLS ANBF Algorithm --- p.37 / Chapter 4.4 --- Performance Study --- p.39 / Chapter 4.4.1 --- Relationship to LMS ANBF and Bandwidth Evaluation . --- p.39 / Chapter 4.4.2 --- Estimation Error of Tap Weights --- p.40 / Chapter 4.4.3 --- Residual Noise Power of Bandpass Output --- p.42 / Chapter 4.5 --- Simulation Examples --- p.43 / Chapter 4.5.1 --- Estimation of Single Sinusoid in Gaussian White Noise . --- p.43 / Chapter 4.5.2 --- Comparing the Performance of IIR Filter and ANBFs . . --- p.44 / Chapter 4.5.3 --- Harmonic Signal Enhancement --- p.45 / Chapter 4.5.4 --- Cancelling 50/60Hz Interference in ECG signal --- p.46 / Chapter 4.6 --- Simulation Results of Performance Study --- p.52 / Chapter 4.6.1 --- Bandwidth --- p.52 / Chapter 4.6.2 --- Estimation Errors --- p.53 / Chapter 4.7 --- Concluding Summary --- p.55 / Chapter 4.8 --- Appendix A: Derivation of Ts --- p.56 / Chapter 4.9 --- Appendix B: Derivation of XT(n)Λ(n)ΛT(n)X(n) --- p.56 / Chapter 5 --- Investigation of the Performance of two Conventional DPOAE Estimation Methods --- p.58 / Chapter 5.1 --- Motivation --- p.58 / Chapter 5.2 --- The DPOAE Signal Model --- p.59 / Chapter 5.3 --- Preliminaries to the Conventional Methods --- p.60 / Chapter 5.3.1 --- Conventional Method 1: Constrained Stimulus Generation --- p.60 / Chapter 5.3.2 --- Conventional Method 2: Windowing --- p.61 / Chapter 5.4 --- Performance Comparison --- p.63 / Chapter 5.4.1 --- Sidelobe Level Reduction --- p.63 / Chapter 5.4.2 --- Estimation Accuracy --- p.65 / Chapter 5.4.3 --- Noise Floor Level --- p.67 / Chapter 5.4.4 --- Additional Loss by Scalloping --- p.68 / Chapter 5.5 --- Simulation Study --- p.69 / Chapter 5.5.1 --- Sidelobe Suppressions of the Windows --- p.69 / Chapter 5.5.2 --- Mean Level Estimation --- p.70 / Chapter 5.5.3 --- Mean Squared Error Analysis --- p.71 / Chapter 5.6 --- Concluding Summary --- p.75 / Chapter 5.7 --- Discussion --- p.75 / Chapter 5.8 --- Appendix A: Cramer-Rao Bound of the DPOAE Level Estimation --- p.76 / Chapter 6 --- Theoretical Considerations of Maximum Likelihood Estimation for the DPOAEs --- p.77 / Chapter 6.1 --- Motivation --- p.77 / Chapter 6.2 --- Finding of the MLEs --- p.78 / Chapter 6.2.1 --- First Form: Joint Estimation of DPOAE and Artifact Pa- rameter --- p.79 / Chapter 6.2.2 --- Second Form: Artifact Cancellation --- p.80 / Chapter 6.3 --- Relationship of CM1 to MLE --- p.81 / Chapter 6.4 --- Approximating the MLE --- p.82 / Chapter 6.5 --- Concluding Summary --- p.84 / Chapter 6.6 --- Appendix A: Equivalent Forms for the Minimum Least Squares Error --- p.85 / Chapter 7 --- Optimum Estimator Structure and Artifact Cancellation Ap- proaches for the DPOAEs --- p.87 / Chapter 7.1 --- Motivation --- p.87 / Chapter 7.2 --- The Optimum Estimator Structure --- p.88 / Chapter 7.3 --- References and Frequency Offset Effect --- p.89 / Chapter 7.4 --- Artifact Canceling Algorithms --- p.92 / Chapter 7.4.1 --- Least-Squares Canceler --- p.93 / Chapter 7.4.2 --- Windowed-Fourier-Transform Canceler --- p.93 / Chapter 7.4.3 --- FRLS Adaptive Canceler --- p.95 / Chapter 7.5 --- Time-domain Noise Rejection --- p.97 / Chapter 7.6 --- Regional Periodogram --- p.98 / Chapter 7.7 --- Experimental Results --- p.99 / Chapter 7.7.1 --- Artifact Cancellation via External Reference --- p.99 / Chapter 7.7.2 --- Artifact Cancellation via Internal Reference --- p.99 / Chapter 7.7.3 --- Artifact Cancellation in presence of Transient Noise --- p.101 / Chapter 7.7.4 --- Illustrative Example: DPgrams --- p.102 / Chapter 7.8 --- Conclusion and Discussion --- p.111 / Chapter 7.9 --- Appendix A: Derivation of the Parabolic Interpolation Method . --- p.113 / Chapter 7.10 --- Appendix B: Derivation of Weighted-Least-Squares Canceler . . --- p.114 / Chapter 8 --- Conclusions and Future Research Directions --- p.118 / Chapter 8.1 --- Conclusions --- p.118 / Chapter 8.2 --- Future Research Directions --- p.119 / Bibliography --- p.121

Thesis (M. Sc.)--University of Hong Kong, 1998. / Includes bibliographical references (leaf 37-41).

Noise exposure is one of the most prevalent causes of irreversible occupational disease in Sweden and in many other countries. In hearing conservation programs, aimed at preventing noise-induced hearing loss, audiometry is an important instrument to highlight the risks and to assess the effectiveness of the program. A hazardous working environment and persons affected by it can be identified by monitoring the hearing thresholds of individual employees or groups of employees over time. However, in order to evaluate the prevalence of occupational noise-induced hearing loss, relevant reference data of unexposed subjects is needed. The first part of this dissertation concerns the changes in hearing thresholds over three decades in two occupational environments with high noise levels in the province of Östergötland, Sweden: the mechanical and the wood processing industries. The results show a positive trend, with improving median hearing thresholds from the 1970s into the 1990s. However, the hearing loss present also in the best period, during the 1990s, was probably greater than if the occupational noise exposure had not occurred. This study made clear the need for a valid reference data base, representing the statistical distribution of hearing threshold levels in a population not exposed to occupational noise but otherwise comparable to the group under study. In the second part of the dissertation, reference data for hearing threshold levels in women and men aged from 20 to 79 years are presented, based on measurements of 603 randomly selected individuals in Östergötland. A mathematical model is introduced, based on the hyperbolic tangent function, describing the hearing threshold levels as functions of age. The results show an age-related gender difference, with poorer hearing for men in age groups above 50 years. The prevalence of different degree of hearing loss and tinnitus is described for the same population in the third part of the dissertation. The overall prevalence of mild, moderate, severe or profound hearing loss was 20.9% collectively for women and 25.0% collectively for men. Tinnitus was reported by 8.9% of the women and 17.6% of the men. Approximately 2.4% of the subjects under study had been provided with hearing aids. However, about 7.7% were estimated to potentially benefit from hearing aids as estimated from their degree of hearing loss. Noise-induced hearing loss primarily causes damage to the outer hair cells of the inner ear. The fourth and last part of the dissertation evaluates the outer hair cell function, using otoacoustic emission measurements (OAE). Prevalence results from three different measuring techniques are presented: spontaneous otoacoustic emissions (SOAE), transient evoked otoacoustic emissions (TEOAE) and distortion product otoacoustic emissions (DPOAE). Gender and age effects on the recorded emission levels were also investigated. Women showed higher emission levels compared to men and for both women and men the emission levels decreased with increasing age. The results from the OAE recordings were shown to be somewhat affected by the state of the middle ear. The study included tympanometry, and the relation of the outcome ofthis test to the otoacoustic emissions is described, where high middle ear compliance resulted in low emission level. Reference data for the tympanometric measurements are also presented. The results of this project form an essential part of the important work against noiseinduced hearing loss, which needs continuous monitoring. The reference data presented here will provide a valid and reliable data base for the future assessment of hearing tests performed by occupational health centres in Sweden. This data base will in turn prove useful for comparison studies for Sweden as a responsible fellow EU member country setting high standards for work force safety. The statistical distribution of hearing threshold levels as a function of age for men and women in tabulated form is available on the Swedish Work Environment Authority (Arbetsmiljöverket) web site: http://www.av.se/publikationer/bocker/fysiskt/h293.shtm.

published_or_final_version / Speech and Hearing Sciences / Master / Master of Science in Audiology

published_or_final_version / Speech and Hearing Sciences / Master / Master of Science in Audiology