# CCI-Mobile: Signal Processing Advancements for Cochlear Implant Users in Naturalistic Environments > **NIH NIH R01** · UNIVERSITY OF TEXAS DALLAS · 2020 · $238,750 ## Abstract 1 Project Summary/Abstract (30 lines maximum) 2 The main goal of the active award (Specific Aim 4) is to develop a next-generation, flexible, open source, 3 portable and real-time speech processor platform to be shared with the cochlear implant research 4 community. A successful version of the platform (CCi-MOBILE) has already been developed and shared 5 with many academic and private research laboratories around the world. CCi-MOBILE is compatible with 6 clinically available implanted electronics, but it is unique in providing flexibility and real-time capability 7 that is orders of magnitude greater than any existing external speech processors or other available 8 research platforms. 9 There is much interest among the CCi-MOBILE research community, consisting of dozens of users, to 10 expand CCi-MOBILE capabilities and software to promote field testing in realistic listening situations. 11 These include: (i) the ability to conduct remote experiments and data collection across different CCi- 12 MOBILE sites; (ii) conduct experiments and data collection at home and other real-world environments; 13 (iii) implementation of remote stimulation parameter changes in real time; (iv) record and store samples 14 of the acoustic environment; (v) use Ecological Momentary Assessment (EMA), a technique to collect 15 participant responses in their natural environment and close in time to the experience they are reporting. 16 While having all this functionality in a single platform would foster a new paradigm in terms of the 17 research projects that may be possible, there is a risk that such functionality may be developed in 18 incompatible ways across sites. Instead, we propose developing a single, open-source cloud environment 19 for CCi-MOBILE code, algorithms, and data. This will include a database repository whose design is based 20 on FAIR principles. The ability to conduct global crowdsourced experiments across CCi-MOBILE sites will 21 be a major feature that will greatly accelerate the testing and development of novel audio processing 22 algorithms. Importantly, the project will leverage resources available through the NIH STRIDES initiative. 23 Due to our teams’ expertise in related efforts such as those supported by the LENA Foundation or the 24 cloud-based data sharing depository for Apollo-11 audio resources developed by the UTD team, we 25 believe we are in an excellent position to carry out the proposed development work. The supplement 26 would be largely used to engage top-notch computer science and engineering expertise to complement 27 our existing strengths in a way that will facilitate scalable, world-wide improvement in how the CCi-Mobile 28 research interface is utilized. ## Key facts - **NIH application ID:** 10166457 - **Project number:** 3R01DC016839-03S2 - **Recipient organization:** UNIVERSITY OF TEXAS DALLAS - **Principal Investigator:** John H.L. Hansen - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $238,750 - **Award type:** 3 - **Project period:** 2018-05-03 → 2023-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10166457 ## Citation > US National Institutes of Health, RePORTER application 10166457, CCI-Mobile: Signal Processing Advancements for Cochlear Implant Users in Naturalistic Environments (3R01DC016839-03S2). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10166457. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*