A Comparison of Environment Classification Among Premium Hearing Instruments

Impact of auditory environments on language outcomes in children with a cochlear implant

OBJECTIVES

To analyse the effects of auditory environments on receptive and expressive language outcomes in children with a CI.

DESIGN

A single-institution retrospective review was performed. The auditory environments included Speech-Noise, Speech-Quiet, Quiet, Music, and Noise. Hearing Hour Percentage (HHP) and percent total hours were calculated for each environment. Generalised Linear Mixed Models (GLMM) analyses were used to study the effects of auditory environments on PLS Receptive and Expressive scores.

STUDY SAMPLE

Thirty-nine children with CI.

RESULTS

On GLMM, an increase in Quiet HHP and Quiet percent total hours were positively associated with PLS Receptive scores. Speech-Quiet, Quiet, and Music HHP were positively associated with PLS Expressive scores, with only Quiet being significant for percent total hours. In contrast, percent total hours of Speech-Noise and Noise had a significant negative association with PLS Expressive scores.

CONCLUSIONS

This study suggests that more time spent in a quiet auditory environment positively influences PLS Receptive and Expressive scores and that more time listening to speech in quiet and music positively influences PLS Expressive scores. Time spent in environments recognised as Speech-Noise and Noise might negatively impact a child's expressive language outcomes with a CI. Future research is needed to better understand this association.

The Noise Reduction Algorithm May Not Compensate for the Degradation in Output Signal-to-Noise Ratio Caused by Wide Dynamic Range Compression

PURPOSE

Most modern hearing aids (HAs) employ wide dynamic range compression (WDRC) and noise reduction (NR) algorithms. It is known that the nonlinear effects of WDRC and NR cause changes to the output signal-to-noise ratio (SNR) of an HA. However, the relative contributions of WDRC and NR to the nonlinear effects are not fully understood. The current study investigated (a) whether WDRC or NR dominates the nonlinear effects measured at the output of a digital HA and (b) whether the electroacoustic effectiveness of NR depends on WDRC parameters while input SNR and background noise are systematically varied.

METHOD

Test stimuli were Connected Speech Test sentences in multitalker babble noise (2- or 20-talker), presented at input SNRs ranging from -10 to +10 dB. The HA was programmed using multiband WDRC set according to the National Acoustic Laboratories for Nonlinear HA fitting formula 2 prescriptive fits for four standard audiograms and two compression speeds. The NR algorithm of the HA was switched on or off in separate conditions. Nonlinear electroacoustic effects from the WDRC and NR algorithms were assessed by measuring the output SNR of the HA using a phase-inversion technique. To investigate whether there are other factors that may be important besides the output SNR, the Hearing Aid Speech Intelligibility Index and the Hearing Aid Speech Quality Index were applied to the recordings to generate inferences on aided speech intelligibility and perceived speech quality.

RESULTS

Results showed that WDRC dominated the net nonlinear effect at low-input SNRs, and the net nonlinear effect of WDRC and NR was reduced at high-input SNRs. Results also showed that the effectiveness of NR depended on compression parameters. The effectiveness of NR was partially explained by the trend of Hearing Aid Speech Intelligibility Index and Hearing Aid Speech Quality Index scores, potentially indicating that the Hearing Aid Speech Intelligibility Index and Hearing Aid Speech Quality Index scores may capture factors that cannot be captured by the output SNR metric.

CONCLUSIONS

Results suggest that the individual signal-processing stages in an HA should not be considered as independent. Electroacoustic evaluation of WDRC and NR algorithms in isolation is not sufficient to capture the combined nonlinear effect of the two algorithms.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25962541.

Predicting Individual Hearing-Aid Preference From Self-Reported Listening Experiences in Daily Life

OBJECTIVES

The study compared the utility of two approaches for collecting real-world listening experiences to predict hearing-aid preference: a retrospective questionnaire (Speech, Spatial, and Qualities of Hearing Scale [SSQ]) and in-situ Ecological Momentary Assessment (EMA). The rationale being that each approach likely provides different and yet complementary information. In addition, it was examined how self-reported listening activity and hearing-aid data-logging can augment EMAs for individualized and contextualized hearing outcome assessments.

DESIGN

Experienced hearing-aid users (N = 40) with mild-to-moderate symmetrical sensorineural hearing loss completed the SSQ questionnaire and gave repeated EMAs for two wear periods of 2-weeks each with two different hearing-aid models that differed mainly in their noise reduction technology. The EMAs were linked to a self-reported listening activity and sound environment parameters (from hearing-aid data-logging) recorded at the time of EMA completion. Wear order was randomized by hearing-aid model. Linear mixed-effects models and Random Forest models with five-fold cross-validation were used to assess the statistical associations between listening experiences and end-of-trial preferences, and to evaluate how accurately EMAs predicted preference within individuals.

RESULTS

Only 6 of the 49 SSQ items significantly discriminated between responses made for the end-of-trial preferred versus nonpreferred hearing-aid model. For the EMAs, questions related to perception of the sound from the hearing aids were all significantly associated with preference, and these associations were strongest in EMAs completed in sound environments with predominantly low SNR and listening activities related to television, people talking, nonspecific listening, and music listening. Mean differences in listening experiences from SSQ and EMA correctly predicted preference in 71.8% and 72.5% of included participants, respectively. However, a prognostic classification of single EMAs into end-of-trial preference with a Random Forest model achieved a 93.8% accuracy when contextual information was included.

CONCLUSIONS

SSQ and EMA predicted preference equally well when considering mean differences, however, EMAs had a high prognostic classifications accuracy due to the repeated-measures nature, which make them ideal for individualized hearing outcome investigations, especially when responses are combined with contextual information about the sound environment.

Sensorineural hearing loss alters auditory discrimination of natural soundscapes

OBJECTIVE

The ability to discriminate natural soundscapes recorded in a temperate terrestrial biome was measured in 15 hearing-impaired (HI) listeners with bilateral, mild to severe sensorineural hearing loss and 15 normal-hearing (NH) controls.

DESIGN

Soundscape discrimination was measured using a three-interval oddity paradigm and the method of constant stimuli. On each trial, sequences of 2-second recordings varying the habitat, season and period of the day were presented diotically at a nominal SPL of 60 or 80 dB.

RESULTS

Discrimination scores were above chance level for both groups, but they were poorer for HI than NH listeners. On average, the scores of HI listeners were relatively well accounted for by those of NH listeners tested with stimuli spectrally-shaped to match the frequency-dependent reduction in audibility of individual HI listeners. However, the scores of HI listeners were not significantly correlated with pure-tone audiometric thresholds and age.

CONCLUSIONS

These results indicate that the ability to discriminate natural soundscapes associated with changes in habitat, season and period of the day is disrupted but it is not abolished. The deficits of the HI listeners are partly accounted for by reduced audibility. Supra-threshold auditory deficits and individual listening strategies may also explain differences between NH and HI listeners.

Auditory environment diversity quantified using entropy from real-world hearing aid data

Introduction

Using data collected from hearing aid users' own hearing aids could improve the customization of hearing aid processing for different users based on the auditory environments they encounter in daily life. Prior studies characterizing hearing aid users' auditory environments have focused on mean sound pressure levels and proportions of environments based on classifications. In this study, we extend these approaches by introducing entropy to quantify the diversity of auditory environments hearing aid users encounter.

Materials and Methods

Participants from 4 groups (younger listeners with normal hearing and older listeners with hearing loss from an urban or rural area) wore research hearing aids and completed ecological momentary assessments on a smartphone for 1 week. The smartphone was programmed to sample the processing state (input sound pressure level and environment classification) of the hearing aids every 10 min and deliver an ecological momentary assessment every 40 min. Entropy values for sound pressure levels, environment classifications, and ecological momentary assessment responses were calculated for each participant to quantify the diversity of auditory environments encountered over the course of the week. Entropy values between groups were compared. Group differences in entropy were compared to prior work reporting differences in mean sound pressure levels and proportions of environment classifications. Group differences in entropy measured objectively from the hearing aid data were also compared to differences in entropy measured from the self-report ecological momentary assessment data.

Results

Auditory environment diversity, quantified using entropy from the hearing aid data, was significantly higher for younger listeners than older listeners. Entropy measured using ecological momentary assessment was also significantly higher for younger listeners than older listeners.

Discussion

Using entropy, we show that younger listeners experience a greater diversity of auditory environments than older listeners. Alignment of group entropy differences with differences in sound pressure levels and hearing aid feature activation previously reported, along with alignment with ecological momentary response entropy, suggests that entropy is a valid and useful metric. We conclude that entropy is a simple and intuitive way to measure auditory environment diversity using hearing aid data.

Effect of Hearing Aid Technology Level and Individual Characteristics on Listener Outcome Measures

Purpose The purpose of the study was to determine the effect of hearing aid technology level on listener outcome measures. In addition, we aimed to determine if individual characteristics such as noise acceptance and the demands of the listening environment impacted performance and preference. Method A repeated-measures, single-blinded research design was utilized. Twenty-four adults recruited by mail from The University of Tennessee Health Science Center Audiology Clinic participated in this experiment (15 men and nine women). Participants completed two 2-week trial periods using Unitron T Moxi Fit FLEX:TRIAL devices programmed as basic or premium technology levels. A data-logging feature, Log It All (LIA), quantified the demands of the listening environment. At the end of each trial, outcome measures were obtained using Pascoe's High-Frequency Word List, the Hearing in Noise Test, the Quick Speech-in-Noise Test, the Acceptable Noise Level (ANL), the Speech, Spatial and Qualities of Hearing short form, satisfaction ratings, and preference. Results Results for ANL, satisfaction in large groups, and LIA total coverage were significantly improved for the premium devices. Participants who preferred the premium devices received significant improvement with premium devices on the ANL and the speech in small group and speech in large group satisfaction ratings, whereas participants who preferred the basic devices did not receive significant improvement with premium devices on any outcome measure. Participants in more demanding listening environments received significant improvement with premium devices on the ANL, whereas participants in less demanding listening environments did not receive significant improvement with premium devices on any outcome measure. Conclusions Group data revealed similar outcomes between technology levels on most measures; however, noise acceptance and satisfaction for speech in a large group were significantly improved when using the premium devices. Individual characteristics such as noise acceptance and listening demands may be useful when comparing hearing aid technology levels for a given patient.