Evidence map›Paper›PMID 39880674›Full record

ArticleeNeuro2025

Improving Tracking of Selective Attention in Hearing Aid Users: The Role of Noise Reduction and Nonlinearity Compensation.

Johanna Wilroth, Emina Alickovic, Martin A Skoglund, Carine Signoret, Jerker Rönnberg, Martin Enqvist

Abstract read
In one paragraph

Article in eNeuro, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Johanna WilrothAutomatic Control, Department of Electrical Engineering, Linköping University, Linköping 581 83, Sweden Johanna.wilroth@liu.se.ORCID https://orcid.org/0000-0002-1762-7454
Emina AlickovicAutomatic Control, Department of Electrical Engineering, Linköping University, Linköping 581 83, Sweden.ORCID https://orcid.org/0000-0002-4655-9112
Martin A SkoglundAutomatic Control, Department of Electrical Engineering, Linköping University, Linköping 581 83, Sweden.ORCID https://orcid.org/0000-0001-9183-3427
Carine SignoretDisability Research Division, Linnaeus Centre HEAD, Department of Behavioural Sciences and Learning, Linköping University, Linköping 581 83, Sweden.ORCID https://orcid.org/0000-0001-8903-7931
Jerker RönnbergDisability Research Division, Linnaeus Centre HEAD, Department of Behavioural Sciences and Learning, Linköping University, Linköping 581 83, Sweden.ORCID https://orcid.org/0000-0001-7311-9959
Martin EnqvistAutomatic Control, Department of Electrical Engineering, Linköping University, Linköping 581 83, Sweden.ORCID https://orcid.org/0000-0001-6523-8499

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hearing impairment (HI) disrupts social interaction by hindering the ability to follow conversations in noisy environments. While hearing aids (HAs) with noise reduction (NR) partially address this, the "cocktail-party problem" persists, where individuals struggle to attend to specific voices amidst background noise. This study investigated how NR and an advanced signal processing method for compensating for nonlinearities in Electroencephalography (EEG) signals can improve neural speech processing in HI listeners. Participants wore HAs with NR, either activated or deactivated, while focusing on target speech amidst competing masker speech and background noise. Analysis focused on temporal response functions to assess neural tracking of relevant target and masker speech. Results revealed enhanced neural responses (N1 and P2) to target speech, particularly in frontal and central scalp regions, when NR was activated. Additionally, a novel method compensated for nonlinearities in EEG data, leading to improved signal-to-noise ratio (SNR) and potentially revealing more precise neural tracking of relevant speech. This effect was most prominent in the left-frontal scalp region. Importantly, NR activation significantly improved the effectiveness of this method, leading to stronger responses and reduced variance in EEG data and potentially revealing more precise neural tracking of relevant speech. This study provides valuable insights into the neural mechanisms underlying NR benefits and introduces a promising EEG analysis approach sensitive to NR effects, paving the way for potential improvements in HAs.

Indexed as

AttentionHearing AidsHearing LossNoiseSpeech PerceptionAdultAgedElectroencephalographyFemaleHumansMaleMiddle AgedPerceptual MaskingSignal-To-Noise RatioEEGhearing aidsnoisenoise reduction algorithmsnonlinearity compensationtemporal response functions

Identifiers

PMID39880674
PMCPMC11839092

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.