Identification of central auditory processing disorders by scale and entropy features of binaural auditory brainstem potentials

The beta-wave of the binaural interaction component in auditory brainstem responses has been suggested as an objective measure of binaural interaction and has been shown to be of diagnostic value in the diagnosis of the central auditory processing disorder (CAPD). However, a reliable and automated detection of the beta-wave capable of clinical use still remains a challenge. In this correspondence, we introduce a new approach to the identification of the CAPD by scale and entropy features of binaural auditory brainstem potentials. For the feature extraction, we apply adapted tight-frame decompositions which are tailored for a subsequent classification by support vector machines. Our approach provides at least comparable results as the beta detection for the discrimination of patients being at risk for CAPD and patients not being at risk for CAPD but with the major advantage that it is truly objective. Furthermore, as no information from the monaurally evoked potentials is necessary, the measurement cost is reduced by two third compared to the computation of the binaural interaction component. We conclude that a classification of scale and entropy features of binaural auditory brainstem. potentials is very effective for the identification of central auditory processing disorders.