Restoring Perceived Loudness for Listeners With Hearing Loss

Vehicle noise: comparison of loudness ratings in the field and the laboratory

OBJECTIVE

Distorted loudness perception is one of the main complaints of hearing aid users. Measuring loudness perception in the clinic as experienced in everyday listening situations is important for loudness-based hearing aid fitting. Little research has been done comparing loudness perception in the field and in the laboratory.

DESIGN

Participants rated the loudness in the field and in the laboratory of 36 driving actions. The field measurements were recorded with a 360° camera and a tetrahedral microphone. The recorded stimuli, which are openly accessible, were presented in three conditions in the laboratory: 360° video recordings with a head-mounted display, video recordings with a desktop monitor and audio-only.

STUDY SAMPLES

Thirteen normal-hearing participants and 18 hearing-impaired participants with hearing aids.

RESULTS

The driving actions were rated as louder in the laboratory than in the field for the condition with a desktop monitor and for the audio-only condition. The less realistic a laboratory condition was, the more likely it was for a participant to rate a driving action as louder. The field-laboratory loudness differences were bigger for louder sounds.

CONCLUSION

The results of this experiment indicate the importance of increasing realism and immersion when measuring loudness in the clinic.

A flexible data-driven audiological patient stratification method for deriving auditory profiles

For characterizing the complexity of hearing deficits, it is important to consider different aspects of auditory functioning in addition to the audiogram. For this purpose, extensive test batteries have been developed aiming to cover all relevant aspects as defined by experts or model assumptions. However, as the assessment time of physicians is limited, such test batteries are often not used in clinical practice. Instead, fewer measures are used, which vary across clinics. This study aimed at proposing a flexible data-driven approach for characterizing distinct patient groups (patient stratification into auditory profiles) based on one prototypical database (N = 595) containing audiogram data, loudness scaling, speech tests, and anamnesis questions. To further maintain the applicability of the auditory profiles in clinical routine, we built random forest classification models based on a reduced set of audiological measures which are often available in clinics. Different parameterizations regarding binarization strategy, cross-validation procedure, and evaluation metric were compared to determine the optimum classification model. Our data-driven approach, involving model-based clustering, resulted in a set of 13 patient groups, which serve as auditory profiles. The 13 auditory profiles separate patients within certain ranges across audiological measures and are audiologically plausible. Both a normal hearing profile and profiles with varying extents of hearing impairments are defined. Further, a random forest classification model with a combination of a one-vs.-all and one-vs.-one binarization strategy, 10-fold cross-validation, and the kappa evaluation metric was determined as the optimal model. With the selected model, patients can be classified into 12 of the 13 auditory profiles with adequate precision (mean across profiles = 0.9) and sensitivity (mean across profiles = 0.84). The proposed approach, consequently, allows generating of audiologically plausible and interpretable, data-driven clinical auditory profiles, providing an efficient way of characterizing hearing deficits, while maintaining clinical applicability. The method should by design be applicable to all audiological data sets from clinics or research, and in addition be flexible to summarize information across databases by means of profiles, as well as to expand the approach toward aided measurements, fitting parameters, and further information from databases.

Real-World Hearing Aid Usage Patterns and Smartphone Connectivity

Data for monitoring individual hearing aid usage has historically been limited to retrospective questionnaires or data logged intrinsically in the hearing aid cumulatively over time (e. g., days or more). This limits the investigation of longitudinal interactions between hearing aid use and environmental or behavioral factors. Recently it has become possible to analyze remotely logged hearing aid data from in-market and smartphone compatible hearing aids. This can provide access to novel insights about individual hearing aid usage patterns and their association to environmental factors. Here, we use remotely logged longitudinal data from 64 hearing aid users to establish basic norms regarding smartphone connectivity (i.e., comparing remotely logged data with cumulative true hearing aid on-time) and to assess whether such data can provide representative information about ecological usage patterns. The remotely logged data consists of minute-by-minute timestamped logs of cumulative hearing aid on-time and characteristics of the momentary acoustic environment. Using K-means clustering, we demonstrate that hourly hearing aid usage patterns (i.e., usage as minutes/hour) across participants are separated by four clusters that account for almost 50% of the day-to-day variation. The clusters indicate that hearing aids are worn either sparsely throughout the day; early morning to afternoon; from noon to late evening; or across the day from morning to late evening. Using linear mixed-effects regression modeling, we document significant associations between daily signal-to-noise, sound intensity, and sound diversity with hearing aid usage. Participants encounter louder, noisier, and more diverse sound environments the longer the hearing aids are worn. Finally, we find that remote logging via smartphones underestimates the daily hearing aid usage with a pooled median of 1.25 h, suggesting an overall connectivity of 85%. The 1.25 h difference is constant across days varying in total hearing aid on-time, and across participants varying in average daily hearing aid-on-time, and it does not depend on the identified patterns of daily hearing aid usage. In sum, remote data logging with hearing aids has high representativeness and face-validity, and can offer ecologically true information about individual usage patterns and the interaction between usage and everyday contexts.

Auditory Tests for Characterizing Hearing Deficits in Listeners With Various Hearing Abilities: The BEAR Test Battery

The Better hEAring Rehabilitation (BEAR) project aims to provide a new clinical profiling tool-a test battery-for hearing loss characterization. Although the loss of sensitivity can be efficiently measured using pure-tone audiometry, the assessment of supra-threshold hearing deficits remains a challenge. In contrast to the classical "attenuation-distortion" model, the proposed BEAR approach is based on the hypothesis that the hearing abilities of a given listener can be characterized along two dimensions, reflecting independent types of perceptual deficits (distortions). A data-driven approach provided evidence for the existence of different auditory profiles with different degrees of distortions. Ten tests were included in a test battery, based on their clinical feasibility, time efficiency, and related evidence from the literature. The tests were divided into six categories: audibility, speech perception, binaural processing abilities, loudness perception, spectro-temporal modulation sensitivity, and spectro-temporal resolution. Seventy-five listeners with symmetric, mild-to-severe sensorineural hearing loss were selected from a clinical population. The analysis of the results showed interrelations among outcomes related to high-frequency processing and outcome measures related to low-frequency processing abilities. The results showed the ability of the tests to reveal differences among individuals and their potential use in clinical settings.

Toward an Individual Binaural Loudness Model for Hearing Aid Fitting and Development

The individual loudness perception of a patient plays an important role in hearing aid satisfaction and use in daily life. Hearing aid fitting and development might benefit from individualized loudness models (ILMs), enabling better adaptation of the processing to individual needs. The central question is whether additional parameters are required for ILMs beyond non-linear cochlear gain loss and linear attenuation common to existing loudness models for the hearing impaired (HI). Here, loudness perception in eight normal hearing (NH) and eight HI listeners was measured in conditions ranging from monaural narrowband to binaural broadband, to systematically assess spectral and binaural loudness summation and their interdependence. A binaural summation stage was devised with empirical monaural loudness judgments serving as input. While NH showed binaural inhibition in line with the literature, binaural summation and its inter-subject variability were increased in HI, indicating the necessity for individualized binaural summation. Toward ILMs, a recent monaural loudness model was extended with the suggested binaural stage, and the number and type of additional parameters required to describe and to predict individual loudness were assessed. In addition to one parameter for the individual amount of binaural summation, a bandwidth-dependent monaural parameter was required to successfully account for individual spectral summation.

DARF: A data-reduced FADE version for simulations of speech recognition thresholds with real hearing aids

Developing and selecting hearing aids is a time consuming process which is simplified by using objective models. Previously, the framework for auditory discrimination experiments (FADE) accurately simulated benefits of hearing aid algorithms with root mean squared prediction errors below 3 dB. One FADE simulation requires several hours of (un)processed signals, which is obstructive when the signals have to be recorded. We propose and evaluate a data-reduced FADE version (DARF) which facilitates simulations with signals that cannot be processed digitally, but that can only be recorded in real-time. DARF simulates one speech recognition threshold (SRT) with about 30 min of recorded and processed signals of the (German) matrix sentence test. Benchmark experiments were carried out to compare DARF and standard FADE exhibiting small differences for stationary maskers (1 dB), but larger differences with strongly fluctuating maskers (5 dB). Hearing impairment and hearing aid algorithms seemed to reduce the differences. Hearing aid benefits were simulated in terms of speech recognition with three pairs of real hearing aids in silence (≥8 dB), in stationary and fluctuating maskers in co-located (stat. 2 dB; fluct. 6 dB), and spatially separated speech and noise signals (stat. ≥8 dB; fluct. 8 dB). The simulations were plausible in comparison to data from literature, but a comparison with empirical data is still open. DARF facilitates objective SRT simulations with real devices with unknown signal processing in real environments. Yet, a validation of DARF for devices with unknown signal processing is still pending since it was only tested with three similar devices. Nonetheless, DARF could be used for improving as well as for developing or model-based fitting of hearing aids.

Loudness functions for patients with functional hearing loss

OBJECTIVES

To compare the loudness functions (loudness ratings as a function of sound level) obtained from patients diagnosed as having functional hearing loss (FHL) with those for patients with sensorineural hearing loss (SNHL) and healthy volunteers.

DESIGN

Loudness functions for a 1000 Hz tone for patients with FHL and SNHL were assessed based on the categorical loudness scaling method. The data were compared with control data obtained in our facilities.

STUDY SAMPLE

18 patients (33 ears) with FHL and 10 patients (19 ears) with SNHL.

RESULTS

For patients with SNHL and healthy volunteers, loudness increased progressively with increasing sound level above the audiometric threshold, with no exceptions. However, for about 70% of the patients with FHL, a different type of loudness function was obtained; the thresholds determined from the loudness function, which were defined as the minimum sound levels at which loudness could be judged, were 10 dB or more lower than the audiometric threshold (>10 dB), and/or the loudness ratings were elevated for a sound at the audiometric threshold.

CONCLUSIONS

The results support the hypothesis that patients with FHL often make threshold judgments based on a certain loudness.

Towards Auditory Profile-Based Hearing-Aid Fitting: Fitting Rationale and Pilot Evaluation

Background-The clinical characterization of hearing deficits for hearing-aid fitting purposes is typically based on the pure-tone audiogram only. In a previous study, a group of hearing-impaired listeners completed a comprehensive test battery that was designed to tap into different dimensions of hearing abilities. A data-driven analysis of the data yielded four clinically relevant patient sub-populations or "auditory profiles". The purpose of the current study was to propose and pilot-test profile-based hearing-aid settings in order to explore their potential for providing more targeted hearing-aid treatment. Methods-Four candidate hearing-aid settings were developed and evaluated by a subset of the participants tested previously. The evaluation consisted of multi-comparison preference ratings that were carried out in realistic sound scenarios. Results-Listeners belonging to the different auditory profiles showed different patterns of preference for the tested hearing-aid settings that were largely consistent with the expectations. Conclusions-The results of this pilot evaluation support further investigations into stratified, profile-based hearing-aid fitting with wearable hearing aids.

Self-assessment of unilateral and bimodal cochlear implant experiences in daily life

Objective

The subjective experiences were assessed of cochlear implant (CI) users either wearing or not wearing a hearing aid (HA) at the contralateral ear.

Design

Unilateral CI-recipients were asked to fill out a set of daily-life questionnaires on bimodal HA use, hearing disability, hearing handicap and general quality of life.

Study sample

Twenty-six CI-recipients who regularly use a contralateral HA (bimodal group) and twenty-two CI-recipients who do not use a HA in the contralateral ear (unilateral group).

Results

Comparisons between both groups (bimodal versus unilateral) showed no difference in self-rated disability, hearing handicap or general quality of life. However within the group of bimodal listeners, participants did report a benefit of bimodal hearing ability in various daily life listening situations.

Conclusions

Bimodal benefit in daily life can consistently be experienced and reported within the group of bimodal users.

The perceptual limitations of troubleshooting hearing-aids based on patients' descriptions

OBJECTIVES

Hearing-aid frequency-gain responses are routinely adjusted by clinicians to patient preferences and descriptions. This study measured the minimum gain adjustments required to elicit preferences, and the assignment of descriptors to gain adjustments, to perceptually evaluate description-based troubleshooting.

DESIGN

Participants judged whether short sentences with ±0-12 dB gain adjustments in one of three frequency bands were "better", "worse" or "no different" from the same sentence at their individual real-ear or prescribed gain. If judged "better" or "worse", participants were then asked to assign one of the six common sound-quality descriptors to their preference.

STUDY SAMPLE

Thirty-two adults (aged 51-75 years) all with hearing-aid experience.

RESULTS

Median preference thresholds, the minimum gain adjustments to elicit "better" or "worse" judgments, ranged from 4 to 12 dB, increasing with frequency. There was some between-participant agreement in preferences: participants generally preferred greater low-frequency gain. Within-participant reliability for preferences was moderate. There was, however, little between-participant agreement in descriptor selection for gain adjustments. Furthermore, within-participant reliability for descriptor selection was lacking.

CONCLUSIONS

The scale of gain adjustments necessary to elicit preferences, along with the low agreement and reliability in descriptors for these adjustments questions the efficiency and efficacy of current description-based troubleshooting, especially with short speech stimuli.

Uni- and bilateral spectral loudness summation and binaural loudness summation with loudness matching and categorical loudness scaling

OBJECTIVE

Current hearing aid prescription rules assume that spectral loudness summation decreases with hearing impairment and that binaural loudness summation is independent of hearing loss and signal bandwidth. Previous studies have shown that these assumptions might be incorrect. Spectral loudness summation was measured and compared for loudness scaling and loudness matching.

DESIGN

In this study, the effect of bandwidth on binaural summation was investigated by comparing loudness perception of low-pass filtered, high-pass filtered, and broadband pink noise at 35 Categorical Units for both unilateral and bilateral presentation.

STUDY SAMPLE

Sixteen hearing-impaired listeners.

RESULTS

The results show that loudness differences between the three signals are different for bilateral presentation than for unilateral presentation. In specific, binaural loudness summation is larger for the low-pass filtered pink noise than for the high-pass filtered pink noise. Finally, individual variability in loudness perception near loudness discomfort level was found to be very large.

CONCLUSIONS

Loudness matching is offered as a fast and reliable method to measure individual loudness perception. As discomfort with loud sounds is one of the major problems encountered by hearing aid users, measurement of individual loudness perception could improve hearing aid fitting substantially.

Influence of suppression on restoration of spectral loudness summation in listeners with hearing loss

Loudness depends on both the intensity and spectrum of a sound. Listeners with normal hearing perceive a broadband sound as being louder than an equal-level narrowband sound because loudness grows nonlinearly with level and is then summed across frequency bands. This difference in loudness as a function of bandwidth is reduced in listeners with sensorineural hearing loss (SNHL). Suppression, the reduction in the cochlear response to one sound by the simultaneous presentation of another sound, is also reduced in listeners with SNHL. Hearing-aid gain that is based on loudness measurements with pure tones may fail to restore normal loudness growth for broadband sounds. This study investigated whether hearing-aid amplification that mimics suppression can improve loudness summation for listeners with SNHL. Estimates of loudness summation were obtained using measurements of categorical loudness scaling (CLS). Stimuli were bandpass-filtered noises centered at 2 kHz with bandwidths in the range of 0.1-6.4 kHz. Gain was selected to restore normal loudness based on CLS measurements with pure tones. Gain that accounts for both compression and suppression resulted in better restoration of loudness summation, compared to compression alone. However, restoration was imperfect, suggesting that additional refinements to the signal processing and gain-prescription algorithms are needed.