# Model-based Cochlear Implant Programming

> **NIH NIH R01** · VANDERBILT UNIVERSITY · 2024 · $604,282

## Abstract

Project Summary
The overarching goal of this project is to develop and validate patient-specific computational models of cochlear
implant (CI) stimulation and to use these models to create patient-customized, MOdel-based CI Programming
(MOCIP) strategies that optimize implant performance. CIs are a neuroprosthetic devices that use an array of
implanted electrodes to stimulated the auditory nerve and induce hearing sensation. With over 500,000 recipients
worldwide, CI are considered the standard of care treatment for severe-to-profound sensory-based hearing loss.
While results with these devices have been remarkably successful, a significant number of CI recipients
experience poor speech understanding, and, even among the best performers, restoration to normal auditory
fidelity is rare. It is estimated that only 5% of those who could benefit from this technology pursue implantation,
in large part due to the high-degree of uncertainty in outcomes. A substantial portion of the variability in outcomes
with CIs is due to a sub-optimal electro-neural interface (ENI); however, approaches for estimating the patient-
specific ENI have thus far been unreliable.
 The overarching hypothesis of this study is that an accurate estimation of the patient-specific ENI can be
obtained with patient-specific computational models and used to customize CI settings for improved and less
variable implant performance. To test this hypothesis, first, novel image processing and patient-specific
anatomical models, which are tuned using biofeedback signals and permit estimating the ENI by determining
which auditory nerve fibers are healthy and localizing which nerve fibers are stimulated by each electrode, will
be developed and validated. Next, the performance of patient-customized MOCIP strategies that aim to address
sub-optimal conditions found in the ENI will be clinically tested. Finally, MOCIP techniques will be automated
and integrated into software that can be deployed into the clinical workflow. Since MOCIP strategies require only
a change of settings on the CI, they work with existing device technology, do not require further surgery, and are
reversible. If successful, a suite of MOCIP techniques that can objectively guide the programming of CIs towards
optimized settings and improve hearing restoration for new and existing CI recipients will be developed in this
project.

## Key facts

- **NIH application ID:** 10834736
- **Project number:** 5R01DC014037-10
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Jack Noble
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $604,282
- **Award type:** 5
- **Project period:** 2014-06-01 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10834736

## Citation

> US National Institutes of Health, RePORTER application 10834736, Model-based Cochlear Implant Programming (5R01DC014037-10). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10834736. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*