High-Speed Holographic Shape and Full-Field Displacement Measurements of the Tympanic Membrane in Normal and Experimentally Simulated Pathological Ears

Preliminary results of classifying otosclerosis and disarticulation using a convolutional neural network trained with simulated wideband acoustic immittance data

Current noninvasive methods of clinical practice often do not identify the causes of conductive hearing loss due to pathologic changes in the middle ear with sufficient certainty. Wideband acoustic immittance (WAI) measurement is noninvasive, inexpensive and objective. It is very sensitive to pathologic changes in the middle ear and therefore promising for diagnosis. However, evaluation of the data is difficult because of large interindividual variations. Machine learning methods like Convolutional neural networks (CNN) which might be able to deal with this overlaying pattern require a large amount of labeled measurement data for training and validation. This is difficult to provide given the low prevalence of many middle-ear pathologies. Therefore, this study proposes an approach in which the WAI training data of the CNN are simulated with a finite-element ear model and the Monte-Carlo method. With this approach, virtual populations of normal, otosclerotic, and disarticulated ears were generated, consistent with the averaged data of measured populations and well representing the qualitative characteristics of individuals. The CNN trained with the virtual data achieved for otosclerosis an AUC of 91.1 %, a sensitivity of 85.7 %, and a specificity of 85.2 %. For disarticulation, an AUC of 99.5 %, sensitivity of 100 %, and specificity of 93.1 % was achieved. Furthermore, it was estimated that specificity could potentially be increased to about 99 % in both pathological cases if stapes reflex threshold measurements were used to confirm the diagnosis. Thus, the procedures' performance is comparable to classifiers from other studies trained with real measurement data, and therefore the procedure offers great potential for the diagnosis of rare pathologies or early-stages pathologies. The clinical potential of these preliminary results remains to be evaluated on more measurement data and additional pathologies.

Material characterization of human middle ear using machine-learning-based surrogate models

This study aims to introduce a novel non-invasive method for rapid material characterization of middle-ear structures, taking into consideration the invaluable insights provided by the mechanical properties of ear tissues. Valuable insights into various ear pathologies can be gleaned from the mechanical properties of ear tissues, yet conventional techniques for assessing these properties often entail invasive procedures that preclude their use on living patients. In this study, in the first step, we developed machine-learning models of the middle ear to predict its responses with a significantly lower computational cost in comparison to finite-element models. Leveraging findings from prior research, we focused on the most influential model parameters: the Young's modulus and thickness of the tympanic membrane and the Young's modulus of the stapedial annular ligament. The eXtreme Gradient Boosting (XGBoost) method was implemented for creating the machine-learning models. Subsequently, we combined the created machine-learning models with Bayesian optimization (BoTorch) for fast and efficient estimation of the Young's moduli of the tympanic membrane and the stapedial annular ligament. We demonstrate that the resultant surrogate models can fairly represent the vibrational responses of the umbo, stapes footplate, and vibration patterns of the tympanic membrane at most frequencies. Also, our proposed material characterization approach successfully estimated the Young's moduli of the tympanic membrane and stapedial annular ligament (separately and simultaneously) with values of mean absolute percentage error of less than 7%. The remarkable accuracy achieved through the proposed material characterization method underscores its potential for eventual clinical applications of estimating mechanical properties of the middle-ear structures for diagnostic purposes.

Effect of sound-induced vibrations of the pinna on head-related transfer functions: Experimental and numerical investigations

Numerical simulations of head-related transfer functions (HRTFs) conventionally assume a rigid boundary condition for the pinna. The human pinna, however, is an elastic deformable body that can vibrate due to incident acoustic waves. This work investigates how sound-induced vibrations of the pinna can affect simulated HRTF magnitudes. The work will motivate the research question by measuring the sound-induced vibrational patterns of an artificial pinna with a high-speed holographic interferometric system. Then, finite element simulations are used to determine HRTFs for a tabletop model of the B&K 5128 head and torso simulator for a number of directions. Two scenarios are explored: one where the pinna is modeled as perfectly rigid, and another where the pinna is modeled as linear elastic with material properties close to that of auricular cartilage. The findings suggest that pinna vibrations have negligible effects on HRTF magnitudes up to 5 kHz. The same conclusion, albeit with less certainty, is drawn for higher frequencies. Finally, the importance of the elastic domain's material properties is emphasized and possible implications for validation studies on dummy heads 1as well as the limitations of the present work are discussed in detail.

Inaccuracies of deterministic finite-element models of human middle ear revealed by stochastic modelling

For over 40 years, finite-element models of the mechanics of the middle ear have been mostly deterministic in nature. Deterministic models do not take into account the effects of inter-individual variabilities on middle-ear parameters. We present a stochastic finite-element model of the human middle ear that uses variability in the model parameters to investigate the uncertainty in the model outputs (umbo, stapes, and tympanic-membrane displacements). We demonstrate: (1) uncertainties in the model parameters can be magnified by more than three times in the umbo and stapes footplate responses at frequencies above 2 kHz; (2) middle-ear models are biased and they distort the output distributions; and (3) with increased frequency, the highly-uncertain regions spatially spread out on the tympanic membrane surface. Our results assert that we should be mindful when using deterministic finite-element middle-ear models for critical tasks such as novel device developments and diagnosis.

Numerical model characterization of the sound transmission mechanism in the tympanic membrane from a high-speed digital holographic experiment in transient regime

A methodology for the development of a finite element numerical model of the tympanic membrane (TM) based on experiments carried out in the time domain on a cadaveric human temporal bone is presented. Using a high-speed digital holographic (HDH) system, acoustically-induced transient displacements of the TM surface are obtained. The procedure is capable to generate and validate the finite element model of the TM by numerical and experimental data correlation. Reverse engineering approach is used to identify key material parameters that define the mechanical response of the TM. Finally, modal numerical simulations of the specimen are performed. Results show the feasibility of the methodology to obtain an accurate model of a specific specimen and to help interpret its behaviour with additional numerical simulations. STATEMENT OF SIGNIFICANCE: Improving knowledge of the dynamic behavior of the tympanic membrane is key to understanding the sound transmission system in human hearing and advance in the treatment of its pathologies. Recently we acquired a new tool to carry out experiments in transient regime by means of digital laser holography, capable of providing a large amount of information in a controlled transient test. In this work, these data are used to develop a methodology that generates a numerical model of the tympanic membrane based on numerical-experimental correlations. It is important to be able to develop models that fit specific patients. In this work, additional modal simulations are also presented that, in addition to validating the results, provide more information on the specimen.

In vivo optical mapping of the tympanic membrane impulse response

The wide frequency range of the human hearing could be narrowed by various pathologies in the middle ear and in the tympanic membrane that lead to conductive hearing loss. Diagnosing such hearing problems is challenging, however, often relying on subjective hearing tests supported by functional tympanometry. Here we present a method for in vivo 2D mapping of the impulse response of the tympanic membrane, and demonstrate its potential on a healthy human volunteer. The imaging technique is based on interferometric spectrally encoded endoscopy, with a handheld probe designed to scan the human tympanic membrane within less than a second. The system obtains high-resolution 2D maps of key functional parameters including peak response, rise and decay times, oscillation bandwidth and resonance frequency. We also show that the system can identify abnormal regions in the membrane by detecting differences in the local mechanical parameters of the tissue. We believe that by offering a full 2D mapping of broad-bandwidth dynamics of the tympanic membrane, the presented imaging modality would be useful for effective diagnosis of conductive hearing loss in patients.

Mammalian middle ear mechanics: A review

The middle ear is part of the ear in all terrestrial vertebrates. It provides an interface between two media, air and fluid. How does it work? In mammals, the middle ear is traditionally described as increasing gain due to Helmholtz’s hydraulic analogy and the lever action of the malleus-incus complex: in effect, an impedance transformer. The conical shape of the eardrum and a frequency-dependent synovial joint function for the ossicles suggest a greater complexity of function than the traditional view. Here we review acoustico-mechanical measurements of middle ear function and the development of middle ear models based on these measurements. We observe that an impedance-matching mechanism (reducing reflection) rather than an impedance transformer (providing gain) best explains experimental findings. We conclude by considering some outstanding questions about middle ear function, recognizing that we are still learning how the middle ear works.

Parameter Identification From Normal and Pathological Middle Ears Using a Tailored Parameter Identification Algorithm

Current clinical practice is often unable to identify the causes of conductive hearing loss in the middle ear with sufficient certainty without exploratory surgery. Besides the large uncertainties due to interindividual variances, only partially understood cause-effect principles are a major reason for the hesitant use of objective methods such as wideband tympanometry in diagnosis, despite their high sensitivity to pathological changes. For a better understanding of objective metrics of the middle ear, this study presents a model that can be used to reproduce characteristic changes in metrics of the middle ear by altering local physical model parameters linked to the anatomical causes of a pathology. A finite-element model is, therefore, fitted with an adaptive parameter identification algorithm to results of a temporal bone study with stepwise and systematically prepared pathologies. The fitted model is able to reproduce well the measured quantities reflectance, impedance, umbo and stapes transfer function for normal ears and ears with otosclerosis, malleus fixation, and disarticulation. In addition to a good representation of the characteristic influences of the pathologies in the measured quantities, a clear assignment of identified model parameters and pathologies consistent with previous studies is achieved. The identification results highlight the importance of the local stiffness and damping values in the middle ear for correct mapping of pathological characteristics and address the challenges of limited measurement data and wide parameter ranges from the literature. The great sensitivity of the model with respect to pathologies indicates a high potential for application in model-based diagnosis.

Analyses of the Tympanic Membrane Impulse Response Measured with High-Speed Holography

The Tympanic Membrane (TM) transforms acoustic energy to ossicular vibration. The shape and the displacement of the TM play an important role in this process. We developed a High-speed Digital Holography (HDH) system to measure the shape and transient displacements of the TM induced by acoustic clicks. The displacements were further normalized by the measured shape to derive surface normal displacements at over 100,000 points on the TM surface. Frequency and impulse response analyses were performed at each TM point, which enable us to describe 2D surface maps of four new TM mechanical parameters. From frequency domain analyses, we describe the (i) dominant frequencies of the displacement per sound pressure based on Frequency Response Function (FRF) at each surface point. From time domain analyses, we describe the (ii) rising time, (iii) exponential decay time, and the (iv) root-mean-square (rms) displacement of the TM based on Impulse Response Function (IRF) at each surface point. The resultant 2D maps show that a majority of the TM surface has a dominant frequency of around 1.5 kHz. The rising times suggest that much of the TM surface is set into motion within 50 µs of an impulsive stimulus. The maps of the exponential decay time of the IRF illustrate spatial variations in damping, the least known TM mechanical property. The damping ratios at locations with varied dominant frequencies are quantified and compared.

Material characterization of thin planar structures using full-field harmonic vibration response measured with stroboscopic holography

We propose a novel material characterization method to estimate the Young's modulus of thin 2-D structures using non-modal noisy single frequency harmonic vibration data measured with holography. The method uses finite-difference discretization to apply the plate equation to all measured pixels inside the boundary of the vibrating structure and then treats the problem as a Bayesian optimization process to find the value of the Young's modulus by minimizing the Euclidian distance between the measured displacement field and repeatedly calculated displacement field using the plate equation. In order to assess the accuracy of the method, ground truth harmonic displacement magnitude fields of different plates were obtained using analytical solutions and the finite-element method and were used to estimate the Young's moduli. We applied Gaussian and non-Gaussian noise with different intensities to assess the robustness and accuracy of the proposed material characterization method in the presence of noise. We demonstrated that for multiple benchmarks for signal to noise ratio of down to 0 dB, our proposed method had errors of less than 5%. We also quantified the effects of uncertainties in the geometrical and material parameters as well as boundary conditions on the estimated Young's modulus. Furthermore, we studied the effects of the mesh size on the runtime and applied the method to experimental holography vibration measurement data of a copper plate.

Rapid imaging of tympanic membrane vibrations in humans

Functional imaging of the human ear is an extremely challenging task because of its minute anatomic structures and nanometer-scale motion in response to sound. Here, we demonstrate noninvasive in vivo functional imaging of the human tympanic membrane under various acoustic excitations, and identify unique vibration patterns that vary between human subjects. By combining spectrally encoded imaging with phase-sensitive spectral-domain interferometry, our system attains high-resolution functional imaging of the two-dimensional membrane surface, within a fraction of a second, through a handheld imaging probe. The detailed physiological data acquired by the system would allow measuring a wide range of clinically relevant parameters for patient diagnosis, and provide a powerful new tool for studying middle and inner ear physiology.

Multiple angle digital holography for the shape measurement of the unpainted tympanic membrane

The shape of the tympanic membrane (TM) plays an important role in sound transmission through the ear for hearing. Previously we developed a high-speed holographic system employing a tunable wavelength laser for rapid TM shape measurement. However, the tunable laser illumination was not sufficient to measure the shape of the unpainted TM due to the semi-transparency of the TM and short exposure time of the camera. This paper presents a new multiple angle illumination technique that allows us to use a higher power single wavelength laser to perform shape measurements on the unpainted TM. Accuracy of the new method is demonstrated by a measure of a step gauge provided by the National Institute of Standards and Technology. We successfully applied the new shape measurement method on a fresh postmortem human TM without any paint.