50 Participants Needed

Noise-Reduction Algorithm for Hearing Loss

Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: Purdue University
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial explores how different hearing-aid technologies can help people understand speech in noisy environments. Participants will test various settings, including a deep neural noise-reduction algorithm, to determine which settings improve hearing amidst background noise. The goal is to identify the most effective noise-reduction methods. Ideal participants are those who wear hearing aids for mild-to-moderate hearing loss, especially if they struggle with high-pitched sounds. As an unphased trial, this study allows participants to contribute to advancements in hearing-aid technology and enhance their own hearing experience.

Do I have to stop taking my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications. It seems focused on hearing aids and noise reduction, so it's unlikely that medications would be affected, but you should confirm with the trial organizers.

What prior data suggests that this noise-reduction algorithm is safe for hearing aid users?

Research shows that the noise-reduction technology in hearing aids is generally user-friendly. Studies have found that these features can improve speech comprehension in noisy environments without major side effects. For instance, one study revealed that participants did not report significant issues while trying different noise-reduction settings.

This technology is not new; it builds on existing methods studied for hearing loss. Although the specific algorithm in this study might differ slightly, past research considers the overall approach safe. Participants in similar studies have used these algorithms without serious problems. Overall, evidence suggests that this treatment is safe for managing hearing loss.12345

Why are researchers excited about this trial?

Unlike traditional hearing aids that amplify sound to help with hearing loss, the deep neural noise-reduction algorithm is designed to enhance the clarity of speech in noisy environments, which is a common challenge for individuals with hearing loss. Most conventional devices struggle to separate speech from background noise effectively. But this algorithm uses advanced machine learning techniques to improve the signal-to-noise ratio, potentially offering clearer sound quality. Researchers are excited because it represents a shift towards smarter, more adaptive hearing support technologies that could significantly improve the quality of life for users.

What evidence suggests that this noise-reduction algorithm is effective for hearing loss?

This trial will compare different noise-reduction technologies for hearing loss. Research has shown that special noise-reduction technology in hearing aids can greatly improve hearing in noisy environments. One study found that people using these advanced hearing aids understood speech more clearly amid background noise. Another study demonstrated that these hearing aids consistently provided good sound quality, regardless of background noise levels. This technology distinguishes between speech and noise, helping users focus on conversations. Overall, evidence supports that this noise-reduction technology can enhance communication for people with hearing loss.12367

Are You a Good Fit for This Trial?

This trial is for individuals with hearing loss who want to test how different noise-reduction settings on hearing aids work in noisy environments. There are no specific inclusion or exclusion criteria provided, so it's open to those interested and likely those who use hearing aids.

Inclusion Criteria

I need a hearing aid due to mild-to-moderate hearing loss.

Exclusion Criteria

I have hearing loss that is due to problems with the ear canal, eardrum, or middle ear.
My hearing is normal.
I have hearing loss related to my nerves.
See 1 more

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Treatment

Participants complete speech-understanding tasks using the dual-sentence paradigm under various noise-reduction settings and signal-to-noise ratios

1-2 hours
1 visit (in-person)

Follow-up

Participants are monitored for safety and effectiveness after treatment

2 weeks

What Are the Treatments Tested in This Trial?

Interventions

  • Deep Neural Noise-Reduction Algorithm

Trial Overview

The study tests a deep neural noise-reduction algorithm in hearing aids at various signal-to-noise ratios (SNR). Participants will try high, low, and off noise reduction settings while listening to speech against different levels of background noise.

How Is the Trial Designed?

2

Treatment groups

Experimental Treatment

Group I: Signal-to-Noise RatioExperimental Treatment3 Interventions
Group II: Hearing Aid Noise-Reduction ProcessingExperimental Treatment3 Interventions

Find a Clinic Near You

Who Is Running the Clinical Trial?

Purdue University

Lead Sponsor

Trials
239
Recruited
72,200+

Oticon

Collaborator

Trials
2
Recruited
100+

Citations

Objective Evaluation of a Deep Learning-Based Noise ...

This study evaluated six distinct hearing aid signal processing strategies, with an emphasis on understanding the performance of a new DNN-based ...

Evaluating a Deep Neural Noise-Reduction Algorithm for ...

This study is designed to understand how different hearing-aid noise-reduction technologies affect a listener's ability to hear speech in ...

Effectiveness of deep neural networks in hearing aids for ...

Here we evaluated the efficacy of a DNN-based hearing aid signal processing algorithm in improving speech perception in noise (SPIN) in 20 participants with ...

Evaluating Real-World Benefits of Hearing Aids With Deep ...

Hearing aids with DNN-based noise reduction resulted in consistent sound satisfaction regardless of the level of background noise compared to ...

How Does Deep Neural Network-Based Noise Reduction ...

In this study, we evaluated the impact of DNN-based noise reduction program on CI evaluation outcomes in patients with significant hearing loss. To assess ...

Hearing-Loss Compensation Using Deep Neural Networks

This article investigates the use of deep neural networks (DNNs) for hearing-loss compensation. Hearing loss is a prevalent issue affecting ...

Artificial intelligence for hearing loss prevention, diagnosis, ...

AI algorithms can process vast data sets, provide detailed audiograms, and facilitate early detection of hearing impairments. Research shows ...