A sequential detection method for late auditory evoked potentials

This work presents a novel mechanism for detection of late auditory evoked potentials (AEP). AEPs, which are an important diagnostic tool to detect hearing deficiencies, are contained within the electroencephalogram (EEG) at a very low SNR. The authors´ proposed automatic detection of AEPs is based on a Wavelet-Transform of EEG data for feature extraction. Several transform coefficients are then used for a classification by a neural network; its decisions on successive EEG segments are judged by a sequential statistical test. This test stops when a certain confidence is reached to either accept or reject an AEP. Besides providing an objective recognition of AEPs, this procedure can considerably reduce measurement time