Hidden hearing loss, a condition affecting millions, has long been undetectable by conventional hearing tests, leaving those affected without a diagnosis or treatment. This is where the EarDiTech project comes in, funded by the European Innovation Council, with a mission to change this. The project has developed a groundbreaking test that can detect cochlear synaptopathy, a type of hidden hearing loss, and has also created new software for hearing aids that can address this issue.
The inner ear's hair cells play a crucial role in detecting sound, converting vibrations into neural signals that travel to the brain via synaptic connections. Until recently, it was believed that age-related hearing loss primarily affected these hair cells. However, recent research has revealed that the initial damage is often to the synapses, the connections between hair cells and the auditory nerve. This discovery is significant because it highlights the need for a more nuanced understanding of hearing loss.
The standard clinical tool for assessing hearing, the audiogram, measures hair cell performance but fails to capture the synaptic connections' role. This limitation means that audiograms cannot accurately reflect the real-world challenges faced by those with cochlear synaptopathy. The EarDiTech test, on the other hand, combines electrodes placed on the forehead and earlobes with a specially designed audio stimulus, simulating the auditory nerve responses and synaptic connections.
By comparing the size of a patient's response to the normal hearing response, the test can estimate the degree of cochlear synaptopathy. This non-invasive, portable device has shown promise in clinical trials at Ghent University, identifying cochlear synaptopathy across different age groups. The next step is to obtain CE marking, a crucial step towards making the device widely available.
Addressing hidden hearing loss requires more than just detection. The EarDiTech team has developed a software algorithm that modifies incoming sound to stimulate the remaining synapses effectively. This algorithm has shown measurable benefits in patients with cochlear synaptopathy and can run on low battery power and common processing chips, making it suitable for the next generation of hearing aids or even consumer earbuds. The team is now seeking hardware manufacturers to further develop and commercialize their software.
The impact of this research extends beyond the clinic. With a better understanding of the prevalence and progression of hidden hearing loss, health systems can be persuaded to take action. The evidence base gained from long-term studies will be crucial in advocating for better support and treatment options for those affected by this debilitating condition.
