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Objective: The benefit of using smartphones for hearing tests in a non-supervised, rapid, and contactless way has drawn a lot of interest, especially if supra-threshold measures are assessed that go beyond audiogram-based measures alone. It is unclear, nevertheless, how well these measures compare to more supervised and regulated manual audiometric assessments. The aim of this study is to validate such smartphone-based methods against standardised laboratory assessments., Design: Pure-tone audiometry and categorical loudness scaling (CLS) were used. Three conditions with varying degrees of supervision were created and compared. In order to assess binaural and spectral loudness summation, both narrowband monaural and broadband binaural noise have been examined as CLS test stimuli., Study Sample: N  = 21 individuals with normal hearing and N  = 16 participants with mild-to-moderate hearing loss., Results: The tests conducted here did not show any distinctions between smartphone-based and laboratory-based methods., Conclusions: Non-supervised listening tests via smartphone may serve as a valid, reliable, and cost-effective approach, e.g. for pure-tone audiometry, CLS, and the evaluation of binaural and spectral loudness summation. In addition, the supra-threshold tests can be constructed to be invariant against missing calibration and external noise which makes them more robust for smartphone usage than audiogram measures.

Falls are a significant health problem in older people, so preventing them is essential. Since falls are often a consequence of improper reaction to gait disturbances, such as slips and trips, their detection is gaining attention in research. However there are no studies to date that investigated perturbation detection, using everyday wearable devices like hearing aids or smartphones at different body positions. Sixty-six study participants were perturbed on a split-belt treadmill while recording data with hearing aids, smartphones, and professional inertial measurement units (IMUs) at various positions (left/right ear, jacket pocket, shoulder bag, pants pocket, left/right foot, left/right wrist, lumbar, sternum). The data were visually inspected and median maximum cross-correlations were calculated for whole trials and different perturbation conditions. The results show that the hearing aids and IMUs perform equally in measuring acceleration data (correlation coefficient of 0.93 for the left hearing aid and 0.99 for the right hearing aid), which emphasizes the potential of utilizing sensors in hearing aids for head acceleration measurements. Additionally, the data implicate that measurement with a single hearing aid is sufficient and a second hearing aid provides no added value. Furthermore, the acceleration patterns were similar for the ear position, the jacket pocket position, and the lumbar (correlation coefficient of about 0.8) or sternal position (correlation coefficient of about 0.9). The correlations were found to be more or less independent of the type of perturbation. Data obtained from everyday wearable devices appears to represent the movements of the human body during perturbations similar to that of professional devices. The results suggest that IMUs in hearing aids and smartphones, placed at the trunk, could be well suited for an automatic detection of gait perturbations., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Feld et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

MPEG-1 Layer 3 (MP3) is one of the most popular compression formats used for sound and especially for music. However, during the coding process, the MP3 algorithm negatively affects the spectral and dynamic characteristics of the audio file being compressed. The aim of this study is to evaluate the effect the MP3 coding format for different music genres and different bitrates via listening tests in which the original uncompressed files and the compressed files are compared. For this purpose, five different music genres were selected (rock, jazz, electronic, classical and solo instrument), and the files were compressed in three different bitrates (96 kbps, 160 kbps and 320 kbps). The semantic differential method was used, and ten bipolar scales were selected for the listening tests (e.g., better–worse, more distortion–less distortion, etc.). The following are the most important findings of this study: classical music was negatively affected the most among the genres due to the MP3 compression (lowest ratings in 8 out of 10 bipolar scales), the solo instrument was least affected among the genres (highest rating in 7 out of 10 bipolar scales), and for higher bit rates, the differences in ratings were small for all music genres. The findings of this study could be used to optimize and adapt the standard, depending on the music genre and the musical piece that needs to be encoded. [ABSTRACT FROM AUTHOR]

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This article reviews the evolution of a series of models of loudness developed in Cambridge, UK. The first model, applicable to stationary sounds, was based on modifications of the model developed by Zwicker, including the introduction of a filter to allow for the effects of transfer of sound through the outer and middle ear prior to the calculation of an excitation pattern, and changes in the way that the excitation pattern was calculated. Later, modifications were introduced to the assumed middle-ear transfer function and to the way that specific loudness was calculated from excitation level. These modifications led to a finite calculated loudness at absolute threshold, which made it possible to predict accurately the absolute thresholds of broadband and narrowband sounds, based on the assumption that the absolute threshold corresponds to a fixed small loudness. The model was also modified to give predictions of partial loudness-the loudness of one sound in the presence of another. This allowed predictions of masked thresholds based on the assumption that the masked threshold corresponds to a fixed small partial loudness. Versions of the model for time-varying sounds were developed, which allowed prediction of the masked threshold of any sound in a background of any other sound. More recent extensions incorporate binaural processing to account for the summation of loudness across ears. In parallel, versions of the model for predicting loudness for hearingimpaired ears have been developed and have been applied to the development of methods for fitting multichannel compression hearing aids. [ABSTRACT FROM AUTHOR]