EEG based hearing states detection using AR modeling techniques

In this paper, a simple method to determine the hearing threshold state of a subject using the parametric model of EEG time series signal has been investigated. The proposed autoregressive (AR) pole-tracking algorithm tracks the position of the poles and extracts the upper and lower hearing threshold factors of a subject. From the results, for abnormal hearing subjects, the hearing-threshold values are about 40-50 % higher than the normal hearing subjects. The results also show that the hearing threshold factors obtained using AR modeling clearly distinguishes the normal and abnormal hearing states across 20 subjects. The results obtained are promising and it can be used to determine the hearing-threshold state for newborns, infants, and multiple handicaps, a person who lacks verbal communication and behavioral response to the sound stimulation.