Clinical trial NCT06792110: Evaluation of Artificial Intelligence-Integrated Hearing Aids for Individuals with Hearing Loss
Official title: Evaluation of Artificial Intelligence-Integrated Hearing Aids for Individuals with Hearing Loss
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Hearing Loss
Hearing Loss, Sensorineural
Lead sponsor: University of Washington
Sponsor class: OTHER
First posted: 2025-01-24
Enrollment: 100
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Participants will be randomly assigned to groups for each hearing aid device being tested (e.g. commercial model 1, 2, vs study device)
Primary purpose: TREATMENT

Brief summary: The goal of this clinical trial will be to evaluate the efficacy of artificial intelligence-integrated hearing aids in individuals with hearing loss. The main questions to answer are:

1. How effective is an artificial intelligence integrated hearing aid in improving speech perception in noise.
2. How does an artificial intelligence integrated hearing aid compare to currently available commercial hearing aids.

Detailed description: Hearing loss is a leading cause of disability globally. Undertreated hearing loss has been associated with several deleterious sequelae, including social isolation, decreased quality of life, and cognitive decline. For a large portion of individuals with hearing loss, hearing aids remain the intervention of choice for improving communication, decreasing social isolation, and enhancing quality of life. Yet, less than 20% of hearing aid candidates choose to use them2. This is partly due to a perceived lack of benefit from hearing aids. Individuals who use hearing aids continue to report difficulty with speech perception in noisy environments with multiple speakers, such as parties, restaurants, and other complex auditory settings.

The investigators have developed a neural network that runs on-device to achieve real-time target speech hearing in realistic multi-talker environments. Using our neural network, the wearer can focus on speech from a target speaker by learning their unique speech cues while ignoring all interfering speech and noise in complex acoustic environments. The wearer is additionally able to use distance to separate sounds from the environment from target sounds to be amplified. Finally the wearer is also able to specificy categories of sound that will be amplified in environment.

This study will prospectively study a hearing aid implementing these algorithms on individuals with hearing loss. Participants will be randomized to utilizing one of two commercial hearing aids vs the experimental device. Participants will participate in listening tests in which they must identify the words spoken by a specific voice in multi-talker babble noise. The investigators will measure performance with the primary and secondary outcome measures listed elsewhere.

Eligibility criteria: Inclusion Criteria:

* Minimum Age of 18 yo
* Bilateral sensorineural hearing loss amenable to hearing aids
* Able to give informed consent
* Native English speaker
* Able to wear a standard pair of hearing aids

Exclusion Criteria:

* Unable to participate in informed consent
* Use of a cochlear implant
* Hearing loss not amenable to hearing aid use
* Conductive hearing loss

Primary outcomes:
measure: Speech Reception Threshold
timeFrame: From enrollment in the study until completion of a one day listening test experiment.
measure: Awareness of Environmental Marker
timeFrame: From enrollment in the study until completion of a one day listening test experiment.
Secondary outcomes:
measure: Preference Scores
timeFrame: From enrollment in the study until completion of a one day listening test experiment.
measure: Sound quality
timeFrame: 5 minutes
Other outcomes:
Locations:
Study officials:
affiliation: University of Washington
name: Gavriel Kohlberg, MD
role: PRINCIPAL_INVESTIGATOR
References: