Fotios Drakopoulos1, Viacheslav Vasilkov1, Heleen Van Der Biest2, Sarah Verhulst1
1Dept. of Information Technology, Ghent University, 9000 Ghent, Belgium
2Dept. of Rehabilitation Sciences – Audiology, Ghent University, 9000 Ghent, Belgium
With age, our hearing ability starts to decline; communicating in noisy environments becomes challenging, and hearing faint sounds difficult. Part of this decline stems from outer-hair-cell damage, and another factor relates to synaptic damage at the auditory-nerve, i.e., cochlear synaptopathy (CS). Despite the suspected high prevalence of CS among people with self-reported hearing difficulties but normal audiograms, or those with impaired audiograms, conventional hearing-aid algorithms do not specifically compensate for the functional deficits associated with CS. Here, we present and evaluate a number of hearing restoration algorithms that maximally restore auditory-nerve coding in CS-affected peripheries. Using a biophysical model of the auditory periphery, we designed real-time signal-processing algorithms to three different CS types that operate on the time-domain signal. The algorithms preserve the stimulus envelope peaks but modify sound onsets and offsets to increase the resting periods between stimulation. We evaluated our developed algorithms in subjects with and without suspected age-related CS (N=30) to test whether they enhanced envelope-following-responses (EFRs), amplitude-modulation (AM) detection sensitivity and speech intelligibility. Volunteers with normal-hearing (NH) audiograms and ages between 18-25 (yNH) or 45-65 (oNH) y/o participated in our study and the difference between processed and unprocessed stimuli was assessed. Our data show that EFRs and perceptual AM sensitivity were enhanced in both yNH and oNH listeners when using our CS-compensation algorithms. Speech recognition in the Matrix test showed a small improvement that was not consistent across participants, with the yNH group and those with high AM detection sensitivity benefiting the most from the processed speech, suggesting that different approaches might be necessary when applying the algorithms to speech. This new type of sound processing may extend the application range of current hearing-aids and improve temporal envelope processing while leaving sound amplification unaffected.
Acknowledgements: This work was supported by the European Research Council (ERC) under the Horizon 2020 Research and Innovation Programme (grant agreement No 678120 RobSpear).