# CCI-Mobile: Signal Processing Advancements for Cochlear Implant Users in Naturalistic Environments

> **NIH NIH R01** · UNIVERSITY OF TEXAS DALLAS · 2022 · $21,243

## Abstract

1) Project Summary/Abstract
Cochlear prosthesis is widely accepted as the most effective clinical intervention to restore auditory function of
individuals with profound hearing loss. Although state-of-the-art CIs provide a high level of speech
comprehension and aural communication ability to a majority of implant recipients, there remains a major gap
between performance levels of CI users and normal hearing individuals, especially in real-life noisy
environments. This gap in performance in part can be attributed to limitations in both sound coding and
electrical stimulation strategies, and partially due to the limited ability to explore potentially new advanced
algorithms with current CI users in the field. Several methods have been proposed over the years to address
this shortcoming; however, most have been restricted to laboratory research. This is primarily due to the
unavailability of portable sound processing platforms that can 1) implement computationally-intensive sound
processing schemes and 2) assess them chronically in real naturalistic environments. Clinical
processors/platforms are neither powerful, nor flexible to meet the growing scientific needs of the research
community. We propose a multi-center research effort to investigate three complementary sound processing
strategies (Aims 1 – 3), which will be made possible through the proposed research platform (Aim 4). First, we
will develop and test the effectiveness of two new families of front-end speech processing algorithms (Aim 1),
both of which are inspired by speech production/perception physiology and aim to enhance the speech signal
from competing background noise. The potential benefit of these algorithms in real-life acoustic environments
will be assessed by conducting take-home trials using the portable research platform. Next, we will investigate
the potential benefits of real-time user-specified adjustments to frequency allocation and stimulation rate
adjustments on speech perception and sound quality in naturalistic environments (Aim 2). In Aim 3, we will
investigate the effectiveness of speech processing strategies that deliver synchronized electrical stimulation to
bilateral CIs. Specifically, we aim to test differences in ITD discrimination, sound localization, and segregation
of speech in noise with and without synchronized bilateral stimulation. These studies will be done using the
existing prototype of the platform, CCi-MOBILE. As a next step we propose to develop a next-generation CCi-
MOBILE-2 platform - a flexible, open-source, portable sound processing platform that will allow easy
implementation of research ideas as well as long-term assessments of algorithms in real-life acoustic
environments (Aim 4). This one-of-a-kind research platform will be orders of magnitude more flexible and
computationally powerful than existing clinical processors and will aid in bridging scientific research with
commercial applications. The CCi-MOBILE-2 platform will be shared with ...

## Key facts

- **NIH application ID:** 10667673
- **Project number:** 3R01DC016839-05S1
- **Recipient organization:** UNIVERSITY OF TEXAS DALLAS
- **Principal Investigator:** John H.L. Hansen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $21,243
- **Award type:** 3
- **Project period:** 2018-05-03 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10667673

## Citation

> US National Institutes of Health, RePORTER application 10667673, CCI-Mobile: Signal Processing Advancements for Cochlear Implant Users in Naturalistic Environments (3R01DC016839-05S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10667673. Licensed CC0.

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