CompHEAR: A Customizable and Scalable Web-Enabled Auditory Performance Evaluation Platform for Cochlear Implant Sound Processing Research

Author:

Merrill Kris,Muller Leah,Beim Jordan A.,Hehrmann Phillipp,Swan Dean,Alfsmann Daniel,Spahr Tony,Litvak Leo,Oxenham Andrew J.ORCID,Tward Aaron D.ORCID

Abstract

AbstractObjectiveCochlear implants (CIs) are auditory prostheses for individuals with severe to profound hearing loss, offering substantial but incomplete restoration of hearing function by stimulating the auditory nerve using electrodes. However, progress in CI performance and innovation has been constrained by the inability to rapidly test multiple sound processing strategies. Current research interfaces provided by major CI manufacturers have limitations in supporting a wide range of auditory experiments due to portability, programming difficulties, and the lack of direct comparison between sound processing algorithms. To address these limitations, we present the CompHEAR research platform, designed specifically for the Cochlear Implant Hackathon, enabling researchers to conduct diverse auditory experiments on a large scale.Study DesignQuasi-experimentalSettingVirtualMethodsCompHEAR is an open-source, user-friendly platform which offers flexibility and ease of customization, allowing researchers to set up a broad set of auditory experiments. CompHEAR employs a vocoder to simulate novel sound coding strategies for CIs. It facilitates even distribution of listening tasks among participants and delivers real-time metrics for evaluation. The software architecture underlies the platform’s flexibility in experimental design and its wide range of applications in sound processing research.ResultsPerformance testing of the CompHEAR platform ensured that it could support at least 10,000 concurrent users. The CompHEAR platform was successfully implemented during the COVID-19 pandemic and enabled global collaboration for the CI Hackathon (www.cihackathon.com).ConclusionThe CompHEAR platform is a useful research tool that permits comparing diverse signal processing strategies across a variety of auditory tasks with crowdsourced judging. Its versatility, scalability, and ease of use can enable further research with the goal of promoting advancements in cochlear implant performance and improved patient outcomes.

Publisher

Cold Spring Harbor Laboratory

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