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Understanding Variability in Individual Response to Hearing Aid Signal Processing in Wearable Hearing Aids

Souza, Pamela1; Arehart, Kathryn2; Schoof, Tim3; Anderson, Melinda4; Strori, Dorina5,6; Balmert, Lauren7

doi: 10.1097/AUD.0000000000000717
Research Articles
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Objectives: Previous work has suggested that individual characteristics, including amount of hearing loss, age, and working memory ability, may affect response to hearing aid signal processing. The present study aims to extend work using metrics to quantify cumulative signal modifications under simulated conditions to real hearing aids worn in everyday listening environments. Specifically, the goal was to determine whether individual factors such as working memory, age, and degree of hearing loss play a role in explaining how listeners respond to signal modifications caused by signal processing in real hearing aids, worn in the listener’s everyday environment, over a period of time.

Design: Participants were older adults (age range 54–90 years) with symmetrical mild-to-moderate sensorineural hearing loss. We contrasted two distinct hearing aid fittings: one designated as mild signal processing and one as strong signal processing. Forty-nine older adults were enrolled in the study and 35 participants had valid outcome data for both hearing aid fittings. The difference between the two settings related to the wide dynamic range compression and frequency compression features. Order of fittings was randomly assigned for each participant. Each fitting was worn in the listener’s everyday environments for approximately 5 weeks before outcome measurements. The trial was double blind, with neither the participant nor the tester aware of the specific fitting at the time of the outcome testing. Baseline measures included a full audiometric evaluation as well as working memory and spectral and temporal resolution. The outcome was aided speech recognition in noise.

Results: The two hearing aid fittings resulted in different amounts of signal modification, with significantly less modification for the mild signal processing fitting. The effect of signal processing on speech intelligibility depended on an individual’s age, working memory capacity, and degree of hearing loss. Speech recognition with the strong signal processing decreased with increasing age. Working memory interacted with signal processing, with individuals with lower working memory demonstrating low speech intelligibility in noise with both processing conditions, and individuals with higher working memory demonstrating better speech intelligibility in noise with the mild signal processing fitting. Amount of hearing loss interacted with signal processing, but the effects were small. Individual spectral and temporal resolution did not contribute significantly to the variance in the speech intelligibility score.

Conclusions: When the consequences of a specific set of hearing aid signal processing characteristics were quantified in terms of overall signal modification, there was a relationship between participant characteristics and recognition of speech at different levels of signal modification. Because the hearing aid fittings used were constrained to specific fitting parameters that represent the extremes of the signal modification that might occur in clinical fittings, future work should focus on similar relationships with more diverse types of signal processing parameters.

1Department of Communication Sciences and Disorders and Knowles Hearing Center, Northwestern University, Evanston, Illinois, USA

2Department of Speech Language Hearing Sciences, University of Colorado at Boulder

3Department of Speech, Hearing and Phonetic Sciences, Division of Psychology and Language Sciences, University College London

4Department of Otolaryngology, University of Colorado School of Medicine

5Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois, USA

6Department of Linguistics, Northwestern University, Evanston, Illinois, USA

7Department of Preventive Medicine, Biostatistics Collaboration Center, Feinberg School of Medicine, Northwestern University.

Received January 25, 2018; accepted January 25, 2019.

The project was a registered NIH clinical trial (ClinicalTrials.gov Identifier: NCT02448706).

Data management via REDCap is supported at Feinberg School of Medicine by the Northwestern University Clinical and Translational Science (NUCATS) Institute. Research reported in this publication was supported, in part, by grant UL1TR001422 from the National Institutes of Health’s National Center for Advancing Translational Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The project was supported by NIH grant R01 DC012289 (to P. S. and K. A.).

P.S. and K.A. designed and managed the experiment. T. S., M. A., and D. S. performed the experiments. T. S. created and managed the study database and supervised data collection for the Evanston site. M. A. supervised data collection for the Boulder site. T. S. and L. B. performed the statistical analysis. P. S. wrote the main paper. All authors discussed the results and implications and commented on the manuscript at all stages.

Address for correspondence: Pamela Souza, PhD, Communication Sciences and Disorders, Northwestern University, 2240 Campus Drive, Evanston, IL 60201, USA. E-mail: p-souza@northwestern.edu

Online date: April 10, 2019

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