Project description
Innovative technologies for hearing loss diagnosis and treatment
Cochlear Synaptopathy (CS) is the first sign of permanent hearing damage, caused by ageing, excessive exposure to noise or ototoxicity. It affects predominantly communication in background noise and despite its huge prevalence among hearing impaired people, there is currently neither clinical diagnosis nor treatment available. The EU-funded EarDiTech project will further develop the CochSyn test, a differential test based on auditory EEG signals, for the precision diagnosis of CS. At the same time, the project will optimize the CoNNear algorithms for the use in hearing devices, which, based on the outcomes of the CochSyn test, can individually compensate for CS. In addition, clinical trials will provide evidence of the patient benefit and the applicability in a real-world clinical context.
Objective
Cochlear synaptopathy (CS) is a recently discovered type of sensorineural hearing loss (SNHL) that compromises the integrity of the auditory-nerve population after ageing, noise-exposure or ototoxicity. This SNHL type occurs before the gold-standard clinical audiogram detects hearing problems and has functional consequences for neural sound encoding and communication in noisy environments. Despite its presumed high prevalence, CS is neither diagnosed nor treated in clinical practice. There is a WHO-identified need for early-diagnosis and treatment of SNHL to reduce the societal and economic burden of hearing loss, and CS-diagnosis falls within this category. In our ERC StG and PoC projects, we developed a robust, encephalogram-based diagnostic test to quantify CS in humans. Based on this test, we individualize hearing-impaired auditory models to design hearing-aid signal processing that compensates for CS. Our model-based, augmented-hearing algorithms can offer an accessible treatment to those suffering from CS and are based on a clever and versatile neural-network architecture that enables real-time sound processing.
In this project, we plan to implement our diagnostic CS-test (TRL4) in a portable medical device and perform clinical trials with early-adopters and first-point-of-contact centers to demonstrate its patient benefit and application range in a real-world clinical context (TRL5-6). Secondly, we aim to develop hardware demonstrators that embed our augmented-hearing sound processors. These real-time FPGA processors (TRL5) will be tailored for market-entry in the hearable, hearing-aid and cochlear-implant sectors. Along with consolidating our IP portfolio and setting out a business strategy, this challenge on Medical Technology and Devices will enable us to transition our proof-of-concept research discoveries to market with this project: EarDiTech: Precision Hearing Diagnostics and Augmented-hearing Technologies.
Keywords
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
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Call for proposal
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(opens in new window) HORIZON-EIC-2021-TRANSITION-CHALLENGES-01
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9000 Gent
Belgium
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