A Novel Approach for Extracting Important Cues in Complex Auditory Brainstem Response to /da/ Using Fuzzy Model

Gathering an insight into brainstem task in generating auditory response to complex stimuli and its nonlinear behavior can be an important base in auditory system modelling, but no study has been done to demonstrate the nonlinear dynamic behavior of auditory systems considering cABR. This study attends the dynamic modeling of auditory brainstem response to consonant-vowel syllable /da/ using fuzzy logic as nonlinear mapping of the input and output of the system. We recorded cABR to /da/ from 40 normal Farsi speaking subjects in response to /da/ with 40ms duration. This data set was divided to train and validation sets. We implemented a fuzzy logic based model for the dynamic extraction of cABR to /da/ for data set. This model includes singltone fuzzifier, product inference engine and weighted center of average defuzzifier. Rule base representing dynamic of signal was generated and, then, firing rate of each rule was calculated and a histogram of rule firing rate was plotted. We selected the important regions of the histogram regarding to firing pattern of the rule. By choosing an appropriate threshold, a secondary rule reduction was done to generate a simplified model; remaining rules were best rules related to important cues of cABR. This model represents the input-output behavior of the brainstem in generating cABR to consonant-vowel /da/. The total error achieved by cross-validation of the model after an important rule selection is 0.1329 with a variance of 7.08×10-4. Nonlinear fuzzy based dynamic extraction of cABR signal is a valid approach for generating important features of cABR and a remarkable evidence of these signals can be represented by some spatial rules.