Sarah Verhulst

Hearing Technology

The Hearing Technology Lab investigates how sound is encoded in the normal and impaired auditory system, and how this knowledge can be translated into next‑generation diagnostic tools and hearing‑aid algorithms. The work combines auditory neuroscience, computational modelling, psychoacoustics and machine learning to understand how peripheral deficits, such as cochlear synaptopathy (hidden hearing loss) and outer‑hair‑cell dysfunction, shape supra‑threshold sound perception.

A central research line develops biophysically grounded computational models of the human auditory periphery, spanning cochlear mechanics, auditory‑nerve responses and brainstem potentials. These models are used to interpret physiological measurements (EEG, otoacoustic emissions), identify early markers of sensorineural hearing damage, and design personalised hearing‑loss compensation strategies. The lab’s work has been internationally recognised for advancing the mechanistic understanding of hidden hearing loss and its impact on speech‑in‑noise perception.

Complementary research advances EEG‑based and neural‑network–based hearing technologies, including real‑time, personalised hearing‑aid algorithms, model‑based speech enhancement, and closed‑loop systems that adapt to the listener’s auditory profile. The lab also investigates noise‑exposure risks in young and ageing populations, providing evidence‑based insights for public‑health policy.