Brain benefits of deep learning-based noise management in experienced hearing aid users using functional near infrared spectroscopy
Jonathan M. Vaisberg, Carmen Dang, Yan Jiang, Jinyu Qian, Frank A. Russo

TL;DR
This study shows that a deep learning-based hearing aid feature reduces brain effort during listening, as measured by brain oxygenation.
Contribution
The study introduces a novel deep learning-based noise management hearing aid feature and demonstrates its impact on neural activity.
Findings
The DNN-listening program improved listening accuracy compared to standard programs.
The DNN-listening program reduced subjective listening effort and prefrontal oxygenation.
fNIRS confirmed lower oxygenation in the left prefrontal cortex with the DNN program.
Abstract
There is growing interest in using neuroimaging to understanding listening effort in individuals with hearing loss, with a particular focus on how innovative hearing aid features impact listening effort. This study used functional near infrared spectroscopy (fNIRS) to investigate the neural basis of listening effort in experienced hearing aid users. This study evaluated the impact of a new deep learning-based noise management hearing aid feature on cerebral blood oxygenation, with the expectation that it would be associated with less oxygenation in the left prefrontal cortex compared to a standard quiet-listening hearing aid program. Twenty-six experienced hearing aid users repeated sentence-final words from sentences presented in noise while wearing individually prescribed hearing aids in two conditions: a standard-listening program with an omnidirectional microphone setting and a…
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Taxonomy
TopicsHearing Loss and Rehabilitation · Optical Imaging and Spectroscopy Techniques · Music Therapy and Health
