Diagnosis of Auditory Pathologies with Hidden Markov Models
Since about twenty years, the otoneurology functional exploration possesses auditory tool to analyze objectively the state of the nervous conduction of additive pathway. In this paper, we present a new classification approach based on the Hidden Markov Models (HMM) which used to design a Computer aided medical diagnostic (CAMD) tool that asserts auditory pathologies based on Brain-stem Evoked Response Auditory based biomedical test, which provides an effective measure of the integrity of the auditory pathway. Case study, experimental results and comparison with a conventional neural networks models have been reported and discussed.
A new estimator for a four-element plane array is introduced in order to get acoustic-passive direction estimation of targets.We concern much about the performance of the estimator under a two-target situation.In this paper,the two targets concerned are of the same type of acoustic source.Under different signal to interfere ratios,we propose the change of the precision of the direction estimation as the angle between the two targets changes.Our study was done under the real time Warfield situation,and may help the design of small acoustic-passive direction estimation arrays.