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A Bayesian Framework for efficiently steering auditory evoked potential measurements
Josef Schlittenlacher and Steve Bell, David Simpson, Michael Chesnaye (University of Southhampton). September 2021 to August 2023
Characterising a hearing loss is difficult for babies and young children, and relies on time-consuming EEG measurements. Bayesian active learning has shown to reduce testing time considerably in behavioural hearing tests. The same paradigm is applied in this project to the auditory brainstem response, with the aim to reduce the required testing time for Newborn Hearing Screening.