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. Author manuscript; available in PMC: 2023 Mar 1.
Published in final edited form as: Ear Hear. 2021 Aug 11;43(2):563–576. doi: 10.1097/AUD.0000000000001117

Preserving Wideband Tympanometry Information with Artifact Mitigation

Kristine Elisabeth Eberhard 1,2, Michael E Ravicz 1, Gabrielle R Merchant 3, Salwa F Masud 1, Stéphane F Maison 1, Stephen T Neely 3, Hideko Heidi Nakajima 1
PMCID: PMC8855961  NIHMSID: NIHMS1724585  PMID: 34387582

Abstract

Objective:

Absorbance measured using wideband tympanometry (WBT) has been shown to be sensitive to changes in middle- and inner-ear mechanics, with potential to diagnose various mechanical ear pathologies. However, artifacts in absorbance due to measurement noise can obscure information related to pathologies and increase inter-measurement variability. Published reports frequently present absorbance that has undergone smoothing to minimize artifact; however, smoothing changes the true absorbance and can destroy important narrow-band characteristics such as peaks and notches at different frequencies. Because these characteristics can be unique to specific pathologies, preserving them is important for diagnostic purposes. Here, we identify the cause of artifacts in absorbance and develop a technique to mitigate artifacts while preserving the underlying WBT information.

Design:

A newly developed Research Platform for the Interacoustics Titan device allowed us to study raw microphone recordings and corresponding absorbances obtained by WBT measurements. We investigated WBT measurements from normal hearing ears and ears with middle and inner ear pathologies for the presence of artifact and noise. Furthermore, it was used to develop an artifact mitigation procedure and to evaluate its effectiveness in mitigating artifacts without distorting the true WBT information.

Results:

We observed various types of noise that can plague WBT measurements and that contribute to artifacts in computed absorbances, particularly intermittent low-frequency noise. We developed an artifact mitigation procedure that incorporates a high-pass filter and a Tukey window. This artifact mitigation resolved the artifacts from low-frequency noise while preserving characteristics in absorbance in both normal hearing ears and ears with pathology. Furthermore, the artifact mitigation reduced inter-measurement variability.

Conclusions:

Unlike smoothing algorithms used in the past, our artifact mitigation specifically removes artifacts caused by noise. It does not change frequency-response characteristics, such as narrow-band peaks and notches in absorbance at different frequencies that can be important for diagnosis. Also, by reducing inter-measurement variability, the artifact mitigation can improve the test-retest reliability of these measurements.

INTRODUCTION

Middle- and inner-ear disorders that alter the mechanical properties of the ear are common and can result in hearing loss and vestibular dysfunction. However, they can be difficult to diagnose non-invasively or inexpensively (Merchant et al. 1998, Nakajima et al. 2012). Various ear-canal acoustic measurements have been developed to assess the mechanics of the ear, where sound is presented to the ear canal with a calibrated probe and the resulting ear-canal sound pressure is recorded with a microphone. These types of measurements are well summarized in the Eriksholm workshop publications (Feeney 2013).

Current clinical practice utilizes standard tympanometry for assessment of middle-ear mechanics. Standard tympanometry measures the sound pressure of a single tone (most often at 226 Hz) as the static pressure in the ear canal is slowly varied. From this, it derives various outcome measures including compliance, tympanometric peak pressure, and equivalent ear canal volume. (Of note, we use the term “static” for pressure that is slowly varied by the device, similar to how the term is used in tympanometry.) Tympanometry is a sensitive and selective indicator of non-aeration of the middle ear and perforation of the tympanic membrane but is a poor indicator of ossicular disorders (Margolis and Hunter 1999; Nakajima et al. 2005, Rosowski et al. 2012).

Wideband acoustic immittance (WAI) measures the ear canal sound pressure at ambient static pressure in response to a wide range of sound frequencies (from 0.1–0.2 kHz up to 6–20 kHz, depending on the device) (e.g., Keefe et al. 1993; Voss and Allen 1994; Allen et al. 2005; Shahnaz and Bork 2006; Rosowski et al. 2012; Rosowski et al. 2013; Merchant et al. 2019). Use of a wide range of frequencies provides access to more information regarding the mechanics of the middle and inner ear (Feeney et al. 2004; Allen et al. 2005; Feeney et al. 2009; Shahnaz et al. 2009; Beers et al. 2010; Hunter et al. 2010; Rosowski et al. 2012; Kei et al. 2013; Prieve et al. 2013). For example, WAI is sensitive to the presence of ossicular discontinuity, ossicular fixation of different ossicles, tympanic membrane perforation and middle-ear effusion (Feeney et al. 2003; Feeney et al. 2009; Shahnaz et al. 2009; Ellison et al. 2012; Nakajima et al. 2012; Voss et al. 2012; Nakajima et al. 2013; Farahmand et al. 2016; Merchant et al. 2016; Merchant et al. 2019). In newborn hearing screening, WAI can help identify false positives due to non-aerated outer and middle ear cavities from material such as amnionic fluid, mesenchyme, meconium and vernix (Hunter et al. 2008; Voss et al. 2016). Inner-ear lesions such as superior canal dehiscence and change in cerebral spinal fluid pressure can also affect WAI (Voss et al. 2010; Nakajima et al. 2012; Nakajima et al. 2013; Merchant et al. 2015). WAI is measured at ambient ear-canal static pressure, with no pressurization of the ear canal. However, middle-ear static pressure that deviates from the ambient pressure in the ear canal can stiffen the tympanic membrane, thus affecting WAI (Voss et al. 2012; Robinson et al. 2017). The middle-ear pressure can deviate from ambient pressure due to not having recently opened the Eustachian tube (e.g. by swallowing), or Eustachian tube dysfunction that can result from common and intermittent conditions such as nasal congestion due to allergies and viral infection (Shilder et al. 2015).

Wideband tympanometry (WBT) combines WAI and tympanometry to utilize the advantages of each while minimizing the disadvantages. WBT measures ear canal sound pressure in response to a stimulus containing a wide range of acoustic frequencies as static ear-canal pressure is varied. By measuring WAI at many ear-canal static pressures, WBT obtains data when the static pressure difference across the tympanic membrane (between ear canal and middle ear) is minimal and the tympanic membrane therefore is maximally compliant. This ear-canal static pressure at which the tympanic membrane is maximally compliant is called the tympanometric peak pressure (TPP). Using WAI metrics like absorbance at TPP minimizes the influence of middle-ear static pressure on WAI. Consequently, it makes observation of other mechanical pathological changes easier and improves consistency between measurements (Keefe and Levi 1996; Margolis et al. 1999; Keefe and Simmons 2003; Lui et al. 2008; Sanford and Feeney 2008; Sanford et al. 2013; Sun 2016; Feeney et al. 2017). In this way, the clinical utility of WBT is improved compared with WAI at ambient ear-canal static pressure only.

Another advantage of WBT is the potential diagnostic utility of WAI at other static ear-canal pressures. For example, ossicular lesions might be diagnosed more accurately if WAI measurements are compared between TPP and very positive or very negative ear-canal static pressure, in which the TM and attached malleus are pushed medially or pulled distally (Hunter et al. 2017; Feeney et al. 2020). There may also be advantages of a wideband middle-ear muscle reflex measured at TPP compared to standard reflex testing at ambient pressure and 226 Hz (Feeney et al. 2017). Furthermore, wideband middle-ear muscle reflex measured at extreme ear-canal static pressures may improve diagnostic accuracy of ossicular pathologies such as stapes fixation (Dharmarajan et al. 2020). Finally, WBT also provides the clinical information that would be obtained by standard 226 Hz tympanometry.

Despite these advantages, WBT currently has limitations. With ambient-pressure WAI, response averaging is used to reduce noise. However, because Titan’s WBT measurement is performed with a quickly swept continuously-varying ear-canal static pressure, response averaging is not possible. The Titan Standard System (Interacoustics) is the only commercial and FDA-approved device to measure WBT today. It uses Titan Suite software that provides absorbances smoothed across frequency. Published reports of WBT often present results that have been modified, either by averaging across frequency (smoothing) or by averaging across several measurements. We discovered with the new Titan Research Platform (using methods described below), that unsmoothed raw absorbances can vary greatly even between consecutive measurements, and that much of this inter-measurement variability is due to an artifact caused by noise in the measurements. Smoothing (such as performed by the Titan Suite software) can reduce the prominence of the artifacts; however, smoothing and averaging can also change important absorbance characteristics and remove diagnostically useful fine structures. The details of such data modification are not always described in publications, limiting reproducibility, and there is often minimal information on how such modification changes the raw data. Literature also has limited information on “raw” unprocessed WBT data such as microphone recordings in the time domain.

Accurate and complete data are essential for advances in WBT. Preservation of characteristic peaks and notches in absorbance as well as data in the time domain may be important in representing the mechanical characteristics (Merchant et al. 2019; Shah et al. 2020). Future automated diagnostic procedures and diagnostic algorithms utilizing computational modeling and machine learning techniques will likely require unmodified fine structures in the data (Merchant et al. 2019; Sackmann et al. 2019; Masud 2020; Shah et al. 2020).

Importantly, data sharing and comparison of results require transparency and reproducibility in published data. Data sharing will be important for diagnostic procedures requiring large data sets (Shah et al. 2020). Thus, high-quality raw data are necessary. By combining data from several research centers, the diagnostic power of clinical research can be increased.

In this paper, we identify the sources of variability and artifact in absorbance results and develop a method to mitigate them without modifying the true absorbance. Interacoustic’s new Research Platform for the Titan WBT device (described in the Methods section) along with custom software provides access to the microphone output waveform, allowing us to discover low-frequency noise and how it introduces artifacts in the absorbance. In this paper: (1) we present and describe noise in the raw microphone recordings and resulting absorbance artifacts that we have observed in WBT responses in both normal and pathological ears; (2) we describe likely causes of this noise; (3) we develop and present our new artifact mitigation techniques to remove these intermittent artifacts without altering the fine structure of the response, thus allowing us to obtain absorbance similar to measurements that appear not to have been afflicted by these types of noise; (4) finally, by direct comparison between mitigated absorbance and unmitigated raw absorbances without artifact, we confirm that our artifact mitigation is effective and that it preserves the true WBT information.

METHODS

In this section we will describe the Titan’s WBT Standard System and the new Research System that we used to perform calibration and WBT measurements as well as to customize the signal processing. Because the noise, artifact, and other sources of variability arise from measurements and computations, we explain how a WBT measurement was performed, how the WBT signal response was processed, and how WBT metrics, impedance and absorbance, were computed.

The Titan WBT systems

The investigations described here were performed with the commercially-available Titan WBT hardware with the long extension cable (serial number 0964008 v4 Interacoustics, Middelfart, Denmark). This Titan also had the ability to record other measurements such as standard 226 Hz tympanometry and acoustic reflexes, otoacoustic emissions (OAE), and auditory brainstem responses (ABR).

The Titan WBT hardware included a handheld unit with a pump to vary the static ear-canal pressure, and an extension cable with the IOWA probe. The IOWA probe had two sound sources (only one used for WBT) and a microphone to measure sound pressure in the ear canal. Attached to the IOWA probe was a replaceable probe tip (Interacoustics, item #8109405), a rigid tube with four passages (two from the sound sources, one to the microphone, one from the pump). To the probe tip, a disposable soft ear tip (e.g., Sanibel™ mushroom-shaped ear tip, Sanibel Supply, MN, USA) was attached and then inserted into the ear canal.

In this study, we used the new Research System which differs from the Standard System that most investigators have been using to date, as shown in Fig. 1. Both the Standard System and this Research System uses the same hardware (the measuring device and extension cable). For the Standard System, the Titan Suite software includes the Titan IMP440 module that provides a user interface for making measurements and other software that processes the data. This software that comes with the Standard System makes available only modified data such as processed smoothed absorbance. The signal processing methods used by this software are unknown, and this processed output is available only in averaged 1/24th-octave bands rather than at all measured frequencies. In this study, we were interested in the measured raw data before any signal processing is performed by software. To do so, with the new Research System, we used the same commercially-available Titan WBT hardware to perform WBT measurements. We accessed the raw microphone recordings by using the new Research Platform software for our investigations. This allowed us to look at the raw microphone recordings as well as to customize our own software for data analysis and to see the data at intermediate stages such as impedance and reflectance. Although the manufacturer recommended yearly calibration by a representative, in this study we calibrated the system more frequently as described below.

Fig. 1.

Fig. 1.

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Diagram illustrating the Titan Standard System and the new Research System, which was used in this study. The two systems use the same hardware (measuring device and extension cable). The software is different, however: The Standard System uses the Titan Suite software, which makes available only processed smoothed absorbance in 1/24th-octave bands rather than at all measured frequencies. The new Research System used in this study includes the newly available Research Platform software, which allows access to the raw and unmodified microphone recordings by enabling control of the hardware via MATLAB and allowing the user to customize measurements, signal processing and data storage. The Boys Town GUI is our customized user interface for making measurements and saving raw data and is designed using the new Research Platform.

The Titan Research Platform

Interacoustics has shown a commitment to research by developing the new Titan Research Platform. This platform provided us access to the raw measured data, the microphone voltage time record, and enabled development of custom data-acquisition programs. The new Research Platform included a firmware update and a software development kit that enabled control of the hardware via MATLAB (Mathworks, Natick, MA). The development kit allowed great flexibility in the design of customized measurements, signal processing, and data storage paradigms. The group at Boys Town National Research Hospital utilized this development kit to design a graphical user interface (the Boys Town GUI) in MATLAB. The Boys Town GUI replicated the functionality of the Titan Suite while saving the raw microphone output data and the results of intermediate computational steps. This capability enabled us to identify sources of artifact and mitigate them, and to apply the mitigation to existing measurements. We used the new Research Platform and the Boys Town GUI to perform calibrations and WBT measurements, as well as to customize signal processing from the accessible raw data (detailed below).

WBT Measurements

All WBT measurements on subjects were performed at Massachusetts Eye and Ear with approval by the Institutional Review Boards of Massachusetts General Brigham. This study used measurements on subjects with normal hearing (15 ears) as well as with one of two ear pathologies, ossicular discontinuity and superior canal dehiscence (5 ears total). Unless otherwise noted, figure plots are of measurements in normal hearing ears. Normal hearing was confirmed by normal threshold audiometry (25 dB HL or better from 0.25–8 kHz) and 226 Hz tympanometry. The ossicular discontinuity and superior canal dehiscence pathologies were confirmed by surgical exploration and computed tomography imaging, respectively.

We calibrated the IOWA probe at the beginning of each day before making WBT measurements on subjects. Calibration was performed using the Boys Town GUI and new Titan Research Platform with a calibration fixture (Interacoustics item #8507418) as described in Nørgaard et al. (2017). The probe calibration* and the measured microphone response in ears were used to compute ear canal impedance and then absorbance in the same way as the Titan Suite, as described below.

To make a WBT measurement, an appropriate-sized soft ear tip for the ear canal (attached to the probe tip and IOWA probe) was inserted into the ear canal to provide an air-tight seal. During a measurement, the Titan swept the ear-canal static pressure from +200 daPa to –300 daPa over about 1.3 sec. Figure 2A plots the recorded static pressure versus time.

Fig. 2.

Fig. 2.

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Example WBT measurement. (A) During a WBT measurement, static ear-canal pressure varies continuously with time from +200 daPa to about –300 daPa. Plotted dots indicate the static pressures measured at each epoch (defined below). (B) During the static pressure sweep, a train of acoustic click stimuli is presented to the ear canal. Plotted in gray is the raw microphone measurement of a continuous string of acoustic click responses. For analysis, the full measurement is divided into epochs (epochs designated with upper magenta tick marks). Each epoch contains a click response, and a static ear-canal pressure is measured for each epoch (plotted in A). The shaded green epochs denote ~0 daPa and TPP.

While the static pressure was swept, a train of acoustic click stimuli was presented in the ear canal. The acoustic clicks contained energy at frequencies over approximately 0.2 – 8 kHz. The microphone in the IOWA probe measured the acoustic response in the ear canal to the presented click train as well as noise from other sources that might be present in the ear canal. Because the static pressure was swept continuously, each click response was measured at a different static pressure. The sampled static pressures can vary between measurements because the pressure sweep and click response / static pressure recordings were not synchronized due to variations in the static pressure sweep rate and because the starting pressures (around +200 daPa) could vary.

Figure 2B shows an example WBT microphone output waveform that includes the response to 28 acoustic clicks recorded while the static pressure was varied from +200 daPa to –300 daPa. For analysis, the Titan software divided the response into a series of “epochs”, where each epoch contained an individual click response with a corresponding static pressure measurement. In Fig. 2B, epochs are designated by pink vertical tick marks at the top horizontal axis. The epoch in which the recorded static pressure was closest to zero (~0 daPa) was referred to as the “ambient pressure”. TPP was determined consistent with the standard of the Titan’s new Research Platform software, and in a similar manner as in the clinical Titan Suite software (Liu et al. 2008). Specifically, the epoch in which the frequency-averaged (from 0.2 to 2 kHz) absorbance was highest was designated the TPP measurement. The ~0 daPa and TPP epochs in this measurement are labeled in green at the top of Fig. 2B.

Computational Technique

Impedance and absorbance were computed from the microphone voltage recorded in each epoch in a manner similar to that used previously (e.g., Rosowski et al. 2012; Nakajima et al. 2013; Merchant et al. 2020): 1) The spectrum of the microphone response in each epoch was computed from the recorded time waveform. 2) The impedance in the ear canal was computed from the microphone response spectrum using the Thévenin source parameters obtained from the calibration. 3) The absorbance was computed from the impedance, using the default Titan adult value of characteristic impedance based on an ear-canal radius of 3.75 mm. Data were analyzed at all the sampled static pressures. To describe the development and results of our artifact mitigation technique, we primarily used absorbance evaluated at static pressures of ~0 daPa and TPP.

Identifying the Problem

In the Result section, we present examples of raw microphone recordings with noise and the corresponding absorbances that result in artifact. To identify the types of artifacts that contributed to inter-ear variability in absorbance, consecutive measurements and measurements in the same ear with intermittent probe reinsertion were assessed. The corresponding raw microphone recordings were studied to elucidate the nature of the observed variations in absorbance

Signal Processing Technique

In the Results section, we describe our findings of the interaction between the raw microphone recordings with low-frequency noise and the computation of absorbance resulting in artifacts. Analysis of the raw microphone recordings and the method by which absorbance is computed revealed the source of the artifacts we observed. We then describe our new developments of mitigating these artifacts step-by-step. (Because understanding the noise and artifact in the Results section is necessary first, the mitigation process we developed is also described in the Results section afterwards.) We explored various high-pass filters including Chebyshev Type I and Butterworth filters and filter parameters such as bandpass frequency and bandpass ripple. Windowing was also explored, specifically the design and implementation of a Tukey window in order to solve remaining issues while preserving information in the click response.

Validation of the Mitigation Technique

To validate our artifact mitigation technique, measurements before (raw) and after artifact mitigation (mitigated) were compared. First, we compared the raw and mitigated absorbances of measurements with artifact to assess whether the mitigation technique effectively reduced noise in the microphone recording and artifact in the corresponding absorbance. Second, to evaluate for any unwanted effects of mitigation, like introducing additional spurious information, we ensured that in measurements with no apparent artifact, the raw and the mitigated absorbances were similar. We finally compared the mitigated absorbance of measurements with artifacts to absorbance computed from other contemporaneous measurements in which no artifact was apparent. This determined that mitigated waveforms contained the same desired information as waveforms without artifact, the mitigation process did not introduce additional information, and the information that described the mechanics of the ear had not been lost.

RESULTS

In this section, we present what we learned from observing raw microphone recordings and corresponding raw absorbances with artifact. We present the development of our signal processing technique step-by-step, and the results of validating the technique in multiple normal and pathological ears.

Types of Variability in Absorbance Measured with WBT

Fig. 3 shows examples of variability in absorbances measured sequentially in the same ear canal. The first two measurements (1a and 1b) were recorded while the ear tip was kept in place. After removing and re-inserting the ear tip, measurements 2a and 2b were recorded. Subsequent removal and reinsertion of the ear tip resulted in measurements 3a and 3b. This figure shows the two most common types of variability in absorbance: (1) “ripples”, fluctuations with frequency seen most clearly in measurements 1a, 2a, 2b, and 3a; and (2) a vertical shift across frequency, seen in measurements 1a and 2a versus the others. In addition (not shown in Fig. 3), we occasionally saw (3) non-physical absorbance values below 0 (e.g. in Fig. 4B) and (4) large closely-spaced fluctuations with frequency (e.g. in Fig. 10B).

Fig. 3.

Fig. 3.

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Example of six raw absorbances computed from raw microphone measurements (without artifact mitigation) in the same ear. Measurements 1a and 1b were recorded sequentially with the same ear tip insertion. After re-insertion of ear tip, 2a and 2b were measured. Recordings 3a and 3b were after another ear tip re-insertion. Inter-measurement variations in absorbances were seen: while 1b and 3b were mostly smooth, other measurements had fluctuations across frequency; also, 1a and 2a were higher below 2 kHz than the other measurements. (Absorbances shown were at ~0 daPa.)

Fig. 4.

Fig. 4.

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Artifact mitigation of absorbances from measurements with low frequency noise. (A) A raw microphone measurement (gray) with low-frequency noise around 25 ms, resulting in a non-zero value at the end of the epoch (different than that at the beginning). (C) Raw microphone output (gray) was non-zero at the beginning of the epoch and near zero at the end. (B, D) Absorbances (gray) computed from these raw measurements exhibit artifact ripples across frequency due to the mismatched beginning and end of the time waveforms. (A, C, E) The artifact mitigation involved applying a high-pass filter, a Tukey window with zero-padding after ~30 ms (plotted with green dotted line on right y-axis), and a delay of 1.8 ms. The click responses after artifact mitigation (orange) show decreased low-frequency noise and are zero at the beginning and end of the epoch. (B, D, F) The corresponding mitigated absorbances (orange) show reduced artifact. (E) This example click response has noise in the time period where the Tukey window has a value of 1. After mitigation (orange), this noise has been reduced by the high-pass filter but not eliminated. (F) The corresponding raw (gray) and mitigated (orange) absorbances show that the mitigation reduced artifact but did not eliminate variations at the lowest frequencies. (Static pressures: −105 daPa for A & B; −122 daPa=TPP for C & D; −12 daPa =TPP for E & F)

Fig. 10.

Fig. 10.

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Noise of large spike: (A) Example microphone waveform containing a large spike, before (gray) and after mitigation (orange). (B) Absorbance computed from the waveform before (gray) and after mitigation (orange) are similar. (Static pressure was +197 daPa.)

The Fig. 3 example demonstrates that variations in absorbance occur even in sequential measurements with stable ear tip position. For example, between 0.5 and 2 kHz, 1a showed ripples while 1b was smoother. The absorbance 3a also had ripples as compared to the smoother 3b. Of these sources of variation, the ripples were most common and problematic and will be addressed first.

Identification of the Source of Ripples: Low-Frequency Noise

We discovered that the ripple artifacts in the absorbance were caused by an interaction of low-frequency noise with the way absorbance is computed. To demonstrate this, we show an example of the raw microphone recording with respect to time in a single epoch in Fig. 4A in gray. This time waveform included: 1) the response to the stimulus click, which began just after 0 ms and had positive and negative peaks of nearly ±100 mV near 4 ms and decaying to nearly zero by 15 ms; and 2) low-frequency noise, which in this example was largest between 25 and 35 ms and was slightly less than 0 mV at the end of the epoch (at 46 ms).

Figure 4B plots the absorbance computed from the raw microphone voltage in Fig. 4A in gray (referred to as “raw”). Note the ripple artifacts of various sizes throughout the frequency range. Note also that the absorbance was <0 at some frequencies below 250 Hz, which is outside the physically-allowable range (between 0–1).

The low-frequency noise had two effects on the computed absorbance. The largest effect was that it caused a mismatch in the value of the time waveform between the beginning and the end of the measurement epoch. In Fig. 4A in gray, the microphone output was approximately 0 mV at the beginning of the waveform but slightly lower (−5 mV) at the end; thus there was a mismatch between beginning and end of an epoch. When the spectrum was computed from the waveform (to compute impedance and then absorbance), this mismatch caused ripples in the spectrum which then appeared in the impedance and absorbance (Fig. 4B in gray) over a wide frequency range. A similar problem occurred with the time waveform in Fig. 4C in gray: the raw microphone output begins at −5 mV and ends at 0 mV, resulting in ripple artifact in Fig. 4D in gray.

Although these mismatches in Figs. 4A & C (between the beginning and end of the epoch) seem small, they are sufficient to cause noticeable artifactual ripples in the absorbance (gray curves in Figs. 4B & 3D) as well as in the impedances (not shown). We do not know the exact cause of the low-frequency noise in the microphone signal in Figs. 4A & 4C gray: Intermittent noise from the device or the subject (including motion, swallowing, etc.) are possibilities. We suspect that the low-frequency noise shown in the examples in Figs. 4A & 4C gray is likely due to the device.

The large low-frequency noise around 35 ms in Fig. 4A gray also caused the absorbance to be <0 at low frequencies in Fig. 4B gray. It can be seen that the waveforms in Figs. 4C & E gray had no such large noise, and the absorbances in Figs. 4D & F gray were >0 at all frequencies.

Development of Artifact Mitigation

To reduce low-frequency noise, we applied a high-pass digital filter† to the waveform. The same filter was applied (in the frequency domain) to the IOWA probe calibration (Thévenin-equivalent source pressure) used to compute ear-canal impedance. Since the computation of impedance (that goes into absorbance) effectively compares the sound pressure in the ear canal to the source pressure of the probe (obtained from calibration), the high-pass filter needs to be applied to both. By doing so, we avoided a mismatch between the filtered waveform and unfiltered probe calibration, which would otherwise result in an artifact (i.e. the absorbance curve shifted by an order of ~0.02 in magnitude above 500 Hz when the filter was only applied to the waveform). This high-pass filtering technique reduced the effects of the low-frequency noise, but did not completely solve the waveform endpoint mismatch issue.

To eliminate the mismatch between the beginning and end of the time waveform within an epoch, we applied a time window to force the waveform endpoints to zero. We implemented a Tukey window with parameters chosen to preserve as much information in the original waveform’s click response without introducing additional artifact from the window edges. The Tukey window is plotted by the dotted green line in Figs. 4A, C & E associated with the right y-axis and had a value of 1 in a broad ~20 ms long center section and 0 at the ends, with a ~5 ms transition between 0 and 1 at each end. The Tukey window was applied by multiplying the time waveform by the value of the Tukey window, so the waveform was not altered in the flat center section of the window but reduced through the transitions to 0 at the ends. Because the microphone click response had decayed by ~30 ms, we could set the window length shorter (~30 ms) than the entire epoch (~46 ms) and set the remainder of the epoch to zero to remove any late noise.

Because the click response occurred early in the measurement epoch, we shifted the microphone waveform 1.8 ms later in time to put the peak of the microphone click response within the unity-valued portion of the Tukey window. We compensated for this time shift by subtracting a delay from the spectrum in the impedance calculations. After mitigation the TPP is recomputed, as the artifact in the raw absorbance may have influenced the original TPP computation.

The effects of the high-pass filtering and Tukey windowing on the microphone waveform are shown in Fig. 4, plots A, C and E. As compared to the original raw and unmitigated waveforms (in gray), the artifact mitigated waveforms (in orange) had suppressed low-frequency noise, and endpoints were at 0 mV. The mitigated waveforms were also shifted 1.8 ms to the right.

Figures 4 B, D, & F show the absorbances computed after application of our artifact mitigation technique (orange) compared to the absorbances computed from the raw microphone recordings (gray). The mitigated absorbances no longer had the ripples seen in the unmitigated raw absorbances.

To demonstrate the effect of our artifact mitigation on the six consecutive measurements originally shown in Fig. 3 (with ripple artifacts), we plotted the artifact-mitigated absorbances in Fig. 5A. As shown in Fig. 5A, the mitigation effectively removed the absorbance ripples. As a consequence, the variability between these absorbance measurements in the same ear were reduced with mitigation. Some variation remained and will be addressed later in the results section. We have checked the effectiveness of our artifact mitigation technique in eliminating absorbance artifact in more than 15 normal ears and get similar results to the representative examples described above.

Fig. 5.

Fig. 5.

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(A) Mitigated absorbances from the same six measurements of Fig. 2 have reduced artifact compared to the raw absorbances of Fig. 2. (Measurements were at ~0 daPa.) (B) Variation in absorbance due to inaccuracy of static pressure estimates. Absorbance at estimated ~0 daPa at 1 kHz plotted against the actual static pressure in the ear canal at the time of the measurement. Note that the ~0 daPa estimate ranged from +7 daPa (measurement 3b) to −9 daPa (measurement 1a), x-axis. The solid gray line is fitted to the points and shows that the variation in absorbance at estimated ~0 daPa is mostly due to the variation in actual static pressure.

Check for Unwanted Effects of Artifact Mitigation

A successful artifact mitigation technique should preserve the information in the original measurement and not introduce any spurious information. To validate our technique, we compared a measurement with little noise and no apparent artifact before and after mitigation. An example is shown of a raw microphone recording with almost no noise (Fig. 6A gray) and almost no ripple in the raw absorbance (Fig. 6B gray). The absorbance after artifact mitigation (Fig. 6B orange) was almost identical to the raw absorbance (Fig. 6B gray). We saw similar results of preserved absorbance characteristics after mitigation of measurements in more than ten normal ears. This suggests that our artifact mitigation has little effect on true data and preserves important frequency-dependent peaks and notches in absorbance.

Fig. 6.

Fig. 6.

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Mitigation does not distort the absorbance in a measurement without appreciable noise. (A) The raw microphone click response (gray) has almost no noise. Mitigated click response is plotted in orange. (B) Absorbance before (gray) and after (orange) mitigation are similar. (Static pressure was ~0 daPa.)

Ears with Pathology

The examples of WBT measurements presented above were recorded from normal hearing ears. We also wanted to determine if our artifact mitigation was effective on measurements from a wide variety of ears, including those with middle- or inner-ear pathology. We investigated if measurements on pathological ears subjected to noise and artifact would also be helped by our artifact mitigation. Here, we show examples from two types of pathologies: ossicular discontinuity and superior canal dehiscence. The absorbance in both these pathologies has been shown to produce features in absorbance (peaks or notches at different frequencies) not seen in normal ears or ears with ossicular fixation (Feeney et al. 2003; Feeney et al. 2009; Nakajima et al. 2012; Voss et al. 2012; Nakajima et al. 2013; Merchant et al. 2015; Farahmand et al. 2016; Merchant et al. 2016; Masud et al. 2019; Merchant et al. 2019).

Figure 7 shows examples of absorbances from an ear with ossicular discontinuity. Ossicular discontinuity can occur throughout the ossicular chain. It can be difficult to diagnose even intra-operatively, especially small fractures that lead to partial discontinuity. Ossicular discontinuity has been shown to increase absorbance with a prominent peak around 400–800 Hz (Feeney et al. 2003; Feeney et al. 2009; Nakajima et al. 2012; Voss et al. 2012; Nakajima et al. 2013; Farahmand et al. 2016; Merchant et al. 2016; Masud et al. 2019; Merchant et al. 2019). Figure 7A (gray) plots the raw absorbance with ripple artifact; Fig. 7B (gray) plots a subsequent measurement with no apparent artifact in the raw absorbance. In Fig. 7A, the artifact ripple in the raw absorbance (gray) was no longer apparent after mitigation (orange). In Fig. 7B, the raw absorbance without artifact (gray) was unchanged after mitigation (brown dashed). Figure 7C superimposes the mitigated absorbances from the first measurement with noise (7A orange) and the subsequent measurement without noise (7B brown dashed), demonstrating that mitigated absorbances from these different measurements were very similar.

Fig. 7.

Fig. 7.

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Two consecutive measurements (M1 and M2) from an ear with ossicular discontinuity. (A) Measurement M1 had low-frequency noise resulting in the raw absorbance (gray) with considerable artifact. Absorbance after mitigation (orange) had reduced artifact. (B) Measurement M2 had no appreciable noise with almost identical raw absorbance and mitigated absorbance without artifact. (C) Mitigated absorbances from M1 in A (orange) and M2 in B (brown) are similar, demonstrating that our mitigation is effective in measurements in pathological ears with ossicular discontinuity, preserving the characteristic features and reducing inter-measurement variability. (Static pressures were at TPP for both measurements.)

Another pathology that results in absorbance with larger than normal fluctuations (peaks and notches), is superior canal dehiscence, a breach in the bone surrounding the superior semicircular canal (Minor et al. 1998). Superior canal dehiscence can cause a variety of vestibular and/or auditory symptoms that are similar to other common otologic pathologies. Therefore, misdiagnosis can occur, and patients can face long periods of inappropriate treatments before a proper diagnosis is made. Superior canal dehiscence has been shown to result in increased absorbance around 1 kHz (Nakajima et al. 2012; Nakajima et al. 2013; Merchant et al. 2015; Merchant et al. 2016). Figure 8 presents (with a similar series of plots as in Fig. 7), absorbances computed from two subsequent measurements in the same ear with superior canal dehiscence. Figure 8A demonstrates how well the mitigated absorbance (orange) removed artifact as compared to the raw absorbance (gray) computed from raw microphone recordings with noise. Figure 8B demonstrates that the artifact mitigation had little effect on absorbance from measurements without noise (raw and mitigated absorbances were similar). Figure 8C shows that the mitigated absorbances computed from different measurements in the same ear with and without noise (orange and brown-dashed absorbances from A & B) were similar.

Fig. 8.

Fig. 8.

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Two consecutive measurements (M1 and M2) from the same ear with superior canal dehiscence. (A) Raw absorbance (gray) with artifact from measurement M1 with low-frequency noise, and mitigated absorbance (orange) with reduced artifact. (B) Measurement M2 without appreciable noise result in raw and mitigated absorbances that are almost the same. (C) Superimposed mitigated absorbances from M1 in A (orange) and M2 in B (brown) are similar, which shows that the artifact mitigation technique is also effective in measurements in pathological ears with superior canal dehiscence. (Static pressures were at TPP for both measurements.)

As shown, WBT measurements recorded from ears with middle- or inner-ear pathology did indeed exhibit similar absorbance artifacts as those in normal ears. The artifact mitigation effectively reduced the artifacts without distorting the true nature of absorbance that contain important characteristics for diagnosing pathology. The artifact mitigation was tested on five pathological ears with similar results as described in the above representative examples.

Sources of Absorbance Variation Not Treatable by the Artifact Mitigation

Though our mitigation can treat much of the ripple artifact in absorbance from low frequency noise, there are other types of noise that result in variations of absorbance artifact that the mitigation cannot treat. Some examples of such noise are presented below.

Figure 9 shows an example of a burst of low-frequency noise that we suspected to be physiologic noise, perhaps due to motion or bodily function of the subject; we referred to this noise as “putative physiologic noise”. The raw microphone recording is plotted in Fig. 9A. Notice a large low-frequency waveform (±25 mV) between about 150 and 350 ms. We suspected that the prolonged noise was from the subject because of its low-frequency content and duration. The spectrum of this noise had components up to 220 Hz, which was above the cutoff frequency of the high-pass filter. Figure 9B shows the absorbance computed from epoch 5 (labeled and shaded in Fig. 9A) where this noise was present. The mitigated absorbance (orange in Fig. 9B) still had large fluctuations and values <0 below 3 kHz, though at higher frequencies it no longer had ripples. The artifact mitigation did not work well for this type of noise occurring at the same time as the click response. In other epochs in this same measurement without this presumed physiologic noise (such as epoch 25, also labeled and shaded in Fig. 9A), mitigation was successful (Fig. 9C).

Fig. 9.

Fig. 9.

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Burst of prolonged low-frequency noise: (A) Example microphone waveform containing low-frequency noise over several consecutive epochs (presumably physiological). (B) From the 5th epoch (labeled in A) with this type of noise, raw absorbance (gray) and mitigated absorbance (orange) both have large artifacts. (C) The 25th epoch for comparison has raw absorbance (gray) with some artifact, and this artifact is no longer visible in the mitigated absorbance (orange). (Static pressures were +221 daPa in B and ~0 daPa in C).

Another noise, rarely seen, was a single large spike in one epoch of the raw microphone waveform (gray), shown in Fig. 10A. The mitigation reduced the spike in the waveform (Fig. 10A orange) but did not solve the effect of this noise on absorbance (Fig. 10B, orange versus gray). The reduction of the spike is a result of the high-pass filter, which has filtered the low-frequency components. The Tukey window has no effect on the spike, because it occurs underneath the flat center section with a value of 1. We were uncertain as to the source of this noise.

For noise such as shown in Figs. 9 & 10 that cannot be mitigated, a possible solution is to identify the presence of artifacts during the measurement and perform additional measurements. We discuss possible solutions for such noise in the Discussion section.

Effect of Variation in Static Pressure between Measurements

Another source of small variation in absorbance between measurements was variations in the static pressures at which the absorbance was recorded. A closer look at consecutive measurements of Fig. 5A showed that, below 2 kHz, the absorbance was about 0.1 higher in measurements 1a and 2a than in the others (at ~0 daPa).

Recall that the static pressure sweep and the acoustic click train were not synchronized and that the recorded static pressure values could have varied between measurements. Also, the spacing between consecutively sampled static pressures was relatively coarse (low resolution). Consequently, the true 0 daPa or TPP may not have been sampled; there could have been a substantial difference between the true 0 daPa or TPP and the static pressure assigned to estimate ~0 daPa or TPP. Therefore, there can be a difference between a WBT measurement at an estimated ~0 daPa and a WAI measurement without static pressure (0 daPa) at the ear canal.

Figure 5B plots the absorbance at a representative frequency (1 kHz in this example) against the actual ear-canal pressure recorded as “~0 daPa”. It can be seen that because ~0 daPa was evaluated at different actual static pressures in different measurements, the resulting absorbances at ~0 daPa varied. The six measurements followed a consistent trend; absorbances increased with decreased static pressure (data points lie close to a line fit). In summary, the variation in ~0 daPa absorbance measurements was a consequence of the low static pressure resolution such that the ~0 daPa absorbance was actually recorded at a small positive or negative static pressure. Addressing this issue is beyond the scope of this study. A possible solution is discussed below.

DISCUSSION

Artifacts and Artifact Mitigation

We have described how the Titan system measures ear-canal sound pressure and computes absorbance from pressure spectra. We have shown that the artifact ripples sometimes seen in the computed absorbance are usually caused by low-frequency noise. Also, we have shown how the ripples arise from a mismatch in the microphone waveform endpoints caused by the noise.

Our artifact mitigation resolves absorbance artifacts from low-frequency noise. The artifact mitigation incorporates a high-pass filter, time delay, Tukey window with zero padding, and phase compensation for all processing. Our mitigation technique reduces absorbance artifacts in normal hearing ears and in ears with pathology such as middle-ear ossicular discontinuity and inner-ear superior canal dehiscence. We verify that artifact mitigation does not change the true absorbance and that it preserves characteristic features in absorbances that represent the mechanics of the ear. This is verified by showing that the absorbances are similar when calculated from mitigated recordings with artifact, raw recordings without artifact, and mitigated recording without artifact.

Limitations – Other Types of Artifacts

Although our mitigation resolves absorbance artifacts from low-frequency noise, there are other types of noise measured by the microphone that result in absorbance artifacts that our mitigation cannot solve. One type, a burst of low-frequency noise, is believed to be physiologic noise produced by the subject and is shown in Fig. 9. Such noise could be generated internally or caused by movement of the subject. Another type of noise is a spike noise, an example of which is shown in Fig. 10.

Similar types of noise are common to other clinical measurements, such as tympanometry, OAE, and ABR. With immediate feedback of the results while measuring, clinicians can notice intermittent bursts of low-frequency noise and large spikes. Measurements can then be repeated. It is also possible to always make several measurements, keeping only those without noise issues. Another solution is to have an automated rejection algorithm that identifies such noise.

Other Issues Contributing to Variable Results

Leaks around the ear tip: After ear tip placement, the ear tip can move as the ear canal pressure changes, or if the subject moves. This movement can cause sound leaks in the ear canal. It has been thought that leaks are less problematic with WBT than with WAI because pressurization is not possible with a leak (Keefe et al. 2015). However, some preliminary WBT measurements we have made have high absorbance at the low frequencies that might be consistent with a leak (according to criteria by Groon et al. 2015). Therefore, the issue regarding leaks during WBT measurements should be studied in a controlled manner in the future. Similar to some noise issues, leaks could be dealt with by feedback of the results including a rejection algorithm followed by repeated measurements.

Variations in ear tip insertion depth between measurements: Absorbance is generally not greatly affected by this issue because it is a normalization of the measured impedance to a characteristic impedance (e.g., Voss and Allen, 1994). However, insertion-depth effects on absorbance have been reported (Voss et al. 2013; Souza et al. 2014; Abur et al. 2014), perhaps related to variations in ear-canal cross-section area with insertion depth (Voss et al. 2013; Fairbank et al. 2020). There may also be slight effects on absorbance due to compliance of the cartilaginous portion of the ear canal wall (Rosowski et al. 2013; Voss et al. 2013).

Variations in ear-canal cross-sectional area: Absorbance calculations compare the measured impedance to a characteristic impedance that is related to ear-canal cross-sectional area. The Titan system uses a standard area, but it is well known that the ear-canal cross-sectional area varies between subjects and along the ear-canal length (Fairbank et al. 2020). If the standard area estimate used to calculate absorbance is inaccurate, errors will appear in absorbance (Voss et al. 2013; Nørgaard et al. 2019). If the eartip is not perpendicular to the ear-canal wall but obliquely angled, the measurement can also be affected (Nørgaard et al., 2019; Scheperle et al. 2011). A means to estimate ear-canal cross-sectional area in individuals could reduce these effects.

Introduction of static pressure due to probe insertion as a concern: A WBT measurement starts by building up static pressure to around +200 daPa, followed by a down sweep to −300 daPa, during which click responses and corresponding static pressures are recorded. Estimate of ~0 daPa is determined as the recorded static pressure closest to 0 daPa, independent of starting pressure or any pressure introduced due to probe insertion.

Imprecision in ~0 daPa and TPP estimates: As shown in Fig. 5B, the actual static pressures of estimates such as ~0 daPa and TPP can vary across measurements due to asynchrony between the acoustic click train and pressure sweep and the coarse resolution of static pressures. Consequently, variation in ~0 daPa and TPP absorbances between measurements is introduced. A possible solution is to increase the static pressure resolution around the pressure of interest (such as 0 daPa or TPP). Because absorbances from repeated measurements are fit well by a linear regression line as in Fig. 5B, measurements may also be interpolated to the desired static pressure. Finally, a possible solution is to monitor the 226-Hz tympanogram to ensure that TPP is captured accurately and repeat measurements if necessary. These are all issues that are of interest to resolve in future studies.

Combining Data from Repeated Measurements

It is still an open question whether WBT data should be averaged across measurements in the same ear or across ears. An absorbance pattern for a certain pathology, such as a narrow-band maxima or minima, has great potential for diagnosis. For example, characteristic peaks due to pathologies were shown in Figs. 7 & 8. Although a narrow-band pattern can occur in a certain frequency band, the frequencies where such patterns occur vary slightly across measurements. Averaging smooths the absorbance and changes the true and important patterns critical for diagnosis, such as narrow-band maxima or minima. Instead of averaging, it is perhaps better to have one representative measurement to capture the true data and characteristics. By implementing the proposed artifact mitigation, it might be advantageous to choose a representative measurement that preserves the true characteristics of the mechanics of the ear. An algorithm could be developed to determine a representative measurement objectively from several measurements.

Improvements to Consider in the Future

Future improvements in the hardware and software used for WBT measurements could further reduce variability between measurements. As mentioned above, slowing the pressure sweep and/or increasing the resolution of static pressure, especially near 0 daPa and TPP, could reduce variability due to imprecision and low resolution. Also, using a chirp stimulus instead of a click stimulus could improve the signal-to-noise ratio. A stimulus with higher-frequency content can also enable high-frequency WAI information to be utilized, with potential for diagnostic accuracy, as we demonstrated previously (Merchant et al. 2019). Using a higher frequency stimulus however may require improved isolation between the input signal and response signal (Nørgaard et al. 2020, Siegel 1995).

Most importantly, establishing a consensus among researchers and clinicians on identical methodology for making, processing and presenting measurements will allow data sharing among laboratories and clinical research sites (Feeney 2013). Such a data sharing platform has been developed and funded by NIH (Voss 2019). This will enable development of new and powerful diagnostic methods that require large amounts of data recorded in a similar manner, like machine learning.

CONCLUSION

Absorbance data reported from clinical WBT measurements have generally been smoothed by various algorithms that can obscure the true nature of the absorbance and remove characteristic features important for diagnosis. Using the custom Boys Town GUI with the new Titan Research Platform, we identified sources of inter-measurement variation and artifact in absorbance from studying the raw microphone recordings. We developed a mitigation technique that reduces variability and artifact while preserving the true absorbance characteristics. Our mitigation works well for measurements in normal ears and ears with mechanical pathology of the middle and inner ear. Unlike smoothing algorithms that change the absorbance characteristics, our artifact mitigation preserves the true nature of the absorbance that represents the mechanics of the ear.

ACKNOWLEDGEMENTS

We thank John J. Rosowski for his invaluable consultation on this work. We thank Denis Fitzpatrick of Boys Town National Research Hospital who developed the Boys Town GUI. Research reported in this publication was supported for GRM by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) under award number P20GM109023. Support was also provided by National Institute on Deafness and other Communication Disorders (NIDCD) of NIH with grant P50DC015857 (StFM). KEE received PhD fellowship from William Demant Foundation. Funding from JJR’s Gudrun Larsen Eliasen and Nels Kristian Eliason Professorship funding purchased the Interacoustics Titan with the WBT Research Platform.

SaFM & StFM (both) provided support for data collection; KEE gathered data; KEE, MER & STN developed the artifact mitigation algorithm; KEE, MER, GRM & HHN drafted the main paper. All authors discussed the results and implications and commented on the manuscript at all stages.

Source of Funding:

We purchased the Titan WBT system and the new Research Platform. Research reported in this publication was supported for GRM by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) under award number P20GM109023. Support was also provided by National Institute on Deafness and other Communication Disorders (NIDCD) of NIH with grant P50DC015857 (StFM). KEE received PhD fellowship from William Demant Foundation. Funding from JJR’s Gudrun Larsen Eliasen and Nels Kristian Eliason Professorship funding purchased the Interacoustics Titan with the WBT Research Platform.

Footnotes

*

The calibration computes Thévenin-equivalent source parameters (impedance and sound pressure) that describe the probe acoustically.

†

We applied a 4th-order Chebyshev Type I infinite-impulse-response (IIR) filter, bandpass frequency 180 Hz, bandpass ripple 0.02 dB using the MATLAB filtfilt function, which acts on the original waveform and the time-reversed to double the effective filter order and eliminate phase dispersion.

Conflicts of interest

The authors have no conflict of interest.

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