  Classical methods for psychometric function estimation either require
excessive measurements or produce only a low-resolution approximation of the
target psychometric function. In this paper, we propose a novel solution for
rapid screening for a change in the psychometric function estimation of a given
patient. We use Bayesian active model selection to perform an automated
pure-tone audiogram test with the goal of quickly finding if the current
audiogram will be different from a previous audiogram. We validate our approach
using audiometric data from the National Institute for Occupational Safety and
Health NIOSH. Initial results show that with a few tones we can detect if the
patient's audiometric function has changed between the two test sessions with
high confidence.
