500 Participants Needed

AI Noise Reduction for Hearing Loss

CR
Overseen ByClinical Research Study Coordinator
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: Mayo Clinic
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)
Approved in 4 JurisdictionsThis treatment is already approved in other countries

Trial Summary

What is the purpose of this trial?

The purpose of this study is to determine if artificial intelligence- based noise reduction can offer objective improvement in hearing and speech perception for hearing impaired patients.

Do I need to stop my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment DEEPSONIC™ Deep Sound Optimized Neural Integrated Chip for hearing loss?

Research shows that using deep learning-based noise reduction, like the DEEPSONIC AI chip, can improve speech understanding in noisy environments for cochlear implant users, which suggests it may help people with hearing loss hear better in similar situations.12345

How is the DEEPSONIC AI chip treatment different from other hearing loss treatments?

The DEEPSONIC AI chip is unique because it uses artificial intelligence to reduce background noise, helping people with hearing loss understand speech better in noisy environments, unlike traditional hearing aids and cochlear implants that struggle in such situations.23567

Research Team

AS

Aniket Saoji, PhD AuD

Principal Investigator

Mayo Clinic

Eligibility Criteria

This trial is for individuals with hearing impairment, whether they are new to using hearing aids or currently use them. It also includes those who have a cochlear implant in one ear and use a hearing aid in the other. People already satisfied with their current hearing aids or unable to follow the study protocol may not qualify.

Inclusion Criteria

Patients with hearing impairment not using hearing aids
Cochlear implant patients with a single-sided implant (using a hearing aid in the opposite ear)
Individuals with hearing impairment currently using hearing aids

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Baseline Testing

Participants undergo baseline testing including single-word and sentence testing to assess hearing and speech perception

1 week
1 visit (in-person)

Treatment

Participants use the Phonak hearing aid with AI-based noise reduction to evaluate improvement in hearing and speech perception

4-6 weeks

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

Treatment Details

Interventions

  • DEEPSONIC™ Deep Sound Optimized Neural Integrated Chip
Trial Overview The trial is testing DEEPSONIC™, an AI-based noise reduction technology integrated into Phonak Hearing Aids. The goal is to see if this advanced feature can improve speech understanding and overall hearing in noisy environments compared to standard models.
Participant Groups
2Treatment groups
Experimental Treatment
Group I: Hearing Aid onlyExperimental Treatment1 Intervention
Patients with hearing impairment who do not have a Cochlear implant
Group II: Cochlear Implant with Hearing AidExperimental Treatment1 Intervention
Patients with hearing impairment who have a single-sided implant (using a hearing aid on the opposite ear)

DEEPSONIC™ Deep Sound Optimized Neural Integrated Chip is already approved in European Union, United States, Canada, Switzerland for the following indications:

🇪🇺
Approved in European Union as DEEPSONIC AI chip for:
  • Hearing impairment
  • Speech perception improvement
🇺🇸
Approved in United States as DEEPSONIC AI chip for:
  • Hearing impairment
  • Speech perception improvement
🇨🇦
Approved in Canada as DEEPSONIC AI chip for:
  • Hearing impairment
  • Speech perception improvement
🇨🇭
Approved in Switzerland as DEEPSONIC AI chip for:
  • Hearing impairment
  • Speech perception improvement

Find a Clinic Near You

Who Is Running the Clinical Trial?

Mayo Clinic

Lead Sponsor

Trials
3,427
Recruited
3,221,000+

Findings from Research

Osseointegrated auditory implants like Baha(®) effectively deliver sound and amplify hearing for patients with conductive or mixed hearing loss and single-sided sensorineural deafness, addressing key challenges in bone conduction hearing.
Recent advancements in technology, such as computer-based fitting software and automatic directional microphones, enhance the hearing performance of Baha users, particularly in noisy environments.
Challenges and recent developments in sound processing for Baha®.Flynn, MC.[2019]
A new deep neural network (DNN) called 'Deep ACE' has been developed to enhance cochlear implant (CI) performance by effectively removing background noise while maintaining the quality of sound coding, which is crucial for users with profound hearing loss.
In tests with eight CI users, Deep ACE significantly improved speech intelligibility scores compared to traditional sound coding strategies, indicating its potential to enhance hearing in noisy environments.
A Deep Denoising Sound Coding Strategy for Cochlear Implants.Gajecki, T., Zhang, Y., Nogueira, W.[2023]
Researchers developed advanced 'smart' hearing aids and cochlear implants using artificial intelligence to effectively filter out background noise, improving speech understanding in noisy environments.
This technology allows individuals with hearing loss to better engage in conversations in challenging settings, such as busy classrooms or restaurants, enhancing their social interactions and quality of life.
Helping People Hear Better with "Smart" Hearing Devices.Goehring, T., Monaghan, J.[2022]

References

Challenges and recent developments in sound processing for Baha®. [2019]
A Deep Denoising Sound Coding Strategy for Cochlear Implants. [2023]
Helping People Hear Better with "Smart" Hearing Devices. [2022]
Successful hearing improvement with direct acoustic stimulation in a patient with schizophrenia. [2018]
Improved Environment-Aware-Based Noise Reduction System for Cochlear Implant Users Based on a Knowledge Transfer Approach: Development and Usability Study. [2021]
The reference ear modeling method for internally feedback controlled digital hearing aid chip. [2020]
Restoring speech intelligibility for hearing aid users with deep learning. [2023]
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