Improving hearing outcomes for cochlear implant users by studying inner ear health
Official title: Improving Cochlear Implant Outcomes Through Modeling and Programming Strategies Based on Human Inner Ear Pathology
Funded at Massachusetts Eye and Ear Infirmary · NIH-10931685 · Data updated 2026-11-12
This study is looking to make cochlear implants work even better for people with severe hearing loss by using smart technology to understand how the implants connect with the inner ear, especially in noisy places, so that we can improve how they help you hear.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts Eye and Ear Infirmary NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | September 18, 2023 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $489,110 |
| NIH project number | 5R01DC021606-02 |
| Project ID | NIH-10931685 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include children and adults who are candidates for cochlear implants or who have already received them.
✕Less likely to help
Patients with normal hearing or those who do not qualify for cochlear implants may not benefit from this research.
What this research studies
This research focuses on enhancing the effectiveness of cochlear implants, which help individuals with severe hearing loss. By using advanced machine learning techniques, the study aims to create detailed 3-D models of the inner ear's neurons and their relationship with cochlear implant electrodes. This will help identify factors that affect hearing performance, particularly in challenging listening environments. The goal is to develop better clinical tools to assess and improve the interface between the cochlear implant and the auditory nerve.
Why it matters
Potential benefit: If successful, this research could lead to improved hearing outcomes for cochlear implant users, allowing them to better understand speech and sounds in various environments.
How similar studies have gone: Previous research has shown promise in using machine learning and advanced modeling techniques to improve medical device outcomes, suggesting potential success for this approach.
Where this research is happening
-
Massachusetts Eye and Ear Infirmary
Boston, United States Active
Researchers
- Principal investigator: Arenberg, Julie G — Massachusetts Eye and Ear Infirmary
- Study coordinator: Arenberg, Julie G
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.