Objective Peak-Detection in Complex Auditory Brainstem Response to /ba/, /da/, /ga/: A Novel Technique

The result of auditory brainstem response is used worldwide for detecting hearing impairments or hearing aids. This study aimed to introduce the superiority of mathematical innovation algorithm toward subjective evaluation by an audiologist. The automatic algorithm method is encouraged for detecting the waves of Auditory Brainstem Response (ABR), because it can reduce subjective evaluation biases and visual analysis errors. This article portrays another technique for automatic detection of the peaks. Finally, by obtaining the standard pattern with this automatic algorithm for Persian speakers, we will compare it with the English speakers whose information was obtained by subjective method in Northwestern University. This article describes the effect of different factors on brainstem responses by performing a new automatic method. Auditory evoked potentials of brainstem activity were recorded by Electro encephalogram (EEG) of 27 Persian speaker adults with normal hearing. Three stimulus /ga/, /da/, and /ba/ were presented. This strategy depends on the utilization of reference wave forms, time latencies, and peaks adjusted and comparison with the ABR. Brainstem response latencies of brainstem peaks were extracted by the automatic method in temporal and spectral domains. This step provides language patterns for Persian speakers. Finally, the results of Persian speakers were compared with the results of a previous study done in Northwestern University by the same recording protocol as our own study on 22 English speaker children. Intraclass correlation coefficients and paired t test were used for evaluating and comparing the results. According to the results, the performance of automatic method is high and reliable. Automatic and visual analysis methods had significant interaction. Latency of auditory brainstem response to the same stimulus in the two study groups was different and had a significant latency. The significance of these discoveries and clinical outcomes of this target strategy are featured in this paper. This simple innovative algorithm could find the correct location of ABR peaks. Because of different acoustic signs and symptoms in the brainstem, the time latencies for all three stimulus used in this study are completely different