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NCT07287774

Evaluating a Deep Neural Noise-Reduction Algorithm for Hearing Aids

Recruiting now NA Last updated 17 December 2025
What this trial tests

NA trial testing Hearing Aid Noise Reduction - Off in Hearing Loss, Cochlear in 50 participants. Currently enrolling.

Timeline
16 October 2025
Primary endpoint
30 April 2026
30 April 2026

Quick facts

Lead sponsorPurdue University
PhaseNA
StatusRecruiting now
Study typeINTERVENTIONAL
Allocationrandomized
Designcrossover
Maskingdouble
Primary purposetreatment
Enrollment50
Start date16 October 2025
Primary completion30 April 2026
Estimated completion30 April 2026
Sites1 location across United States

Drugs / interventions tested

Conditions studied

Sponsor

Purdue University

Who can join

18 and older, any sex, with Hearing Loss, Cochlear. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This study is designed to understand how different hearing-aid noise-reduction technologies affect a listener's ability to hear speech in noisy environments. Participants will listen to speech at several background-noise levels while trying different processing settings. By comparing performance across these conditions, the study aims to identify which types of noise reduction improve speech intelligibility the most. We expect that some noise-reduction strategies will help listeners understand speech better than others, especially in more difficult listening situations.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Hearing Loss, Cochlear

Currently open trials in the same condition.

Other Purdue University trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07287774.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing