Evaluating Real-World Benefits of Hearing Aids With Deep Neural Network--Based Noise Reduction: An Ecological Momentary Assessment Study.

Purpose: Noise reduction technologies in hearing aids provide benefits under controlled conditions. However, differences in their real-life effectiveness are not established. We propose that a deep neural network (DNN)--based noise reduction system trained on naturalistic sound environments will pro...

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Publicado en:American Journal of Audiology Vol. 33; no. 1; pp. 242 - 254
Autores principales: Christensen, Jeppe Høy, Whiston, Helen, Lough, Melanie, Gil-Carvajal, Juan Camilo, Rumley, Johanne, Saunders, Gabrielle H.
Formato: research tables/charts randomized controlled trial Journal Article
Publicado: American Speech-Language-Hearing Association Mar2024
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: American Journal of Audiology
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      dt: Mar2024
      vid: 33
      iid: 1
      pid: 42
      pub: American Speech-Language-Hearing Association
      place: Rockville, Maryland
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        175835752
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        10.1044/2023_AJA-23-00149
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        atl: Evaluating Real-World Benefits of Hearing Aids With Deep Neural Network--Based Noise Reduction: An Ecological Momentary Assessment Study.
      aug:
        au:
          Christensen, Jeppe Høy
          Whiston, Helen
          Lough, Melanie
          Gil-Carvajal, Juan Camilo
          Rumley, Johanne
          Saunders, Gabrielle H.
        affil: Eriksholm Research Centre, Oticon A/S, Snekkersten, Denmark
      sug:
        subj:
          Hearing Aids
          Equipment Design
          Neural Networks (Computer)
          Hearing Loss, Sensorineural Rehabilitation
          Noise Prevention and Control
          Listening Evaluation
          Treatment Outcomes
          Environment
          Human
          Ecological Research
          Funding Source
          Crossover Design
          Randomized Controlled Trials
          Random Assignment
          Comparative Studies
          Adult
          Middle Age
          Aged
          Aged, 80 and Over
          Male
          Female
          Effect Size
          Data Analysis Software
          Descriptive Statistics
          Self Report
          Analysis of Variance
          Chi Square Test
          Correlation Coefficient
          Patient Satisfaction
          Confidence Intervals
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: Purpose: Noise reduction technologies in hearing aids provide benefits under controlled conditions. However, differences in their real-life effectiveness are not established. We propose that a deep neural network (DNN)--based noise reduction system trained on naturalistic sound environments will provide different real-life benefits compared to traditional systems. Method: Real-life listening experiences collected with Ecological Momentary Assessments (EMAs) of participants who used two premium models of hearing aid are compared. One hearing aid model (HA1) used traditional noise reduction; the other hearing aid model (HA2) used DNN-based noise reduction. Participants reported listening experiences several times a day while ambient SPL, SNR, and hearing aid volume adjustments were recorded. Forty experienced hearing aid users completed a total of 3,614 EMAs and recorded 6,812 hr of sound data across two 14-day wear periods. Results: Linear mixed-effects analysis document that participants' assessments of ambient noisiness were positively associated with SPL and negatively associated with SNR but are not otherwise affected by hearing aid model. Likewise, mean satisfaction with the two models did not differ. However, individual satisfaction ratings for HA1 were dependent on ambient SNR, which was not the case for HA2. Conclusions: Hearing aids with DNN-based noise reduction resulted in consistent sound satisfaction regardless of the level of background noise compared to hearing aids implementing noise reduction based on traditional statistical models. While the two hearing aid models also differed on other parameters (e.g., shape), these differences are unlikely to explain the difference in how background noise impacts sound satisfaction with the aids.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        randomized controlled trial
        Journal Article
      ougenre: Article
    language: English
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