A Novel Method for Automated Estimation of Effective Parameters of Complex Auditory Brainstem Response: Adaptive Processing based on Correntropy Concept

Objectives: Automated Auditory Brainstem Responses (ABR) peak detection is a novel technique to facilitate the measurement of neural synchrony along the auditory pathway through the brainstem. Analyzing the location of the peaks in these signals and the time interval between them may be utilized either for analyzing the hearing process or detecting peripheral and central lesions in the human hearing system. Methods: In this paper, model-based signal processing is proposed to estimate effective parameters of ABR signals in which the biological parameters of signal are assessed by utilizing an FIR adaptive filter in which its adaptation procedure is performed based on the correntropy concept. The proposed method is applied on a set of ABR signals recorded in response to three stimuli/da/, /ba/, and /ga/, and then its performances are compared with an existing state-of-the-art technique. Results: The results show that the proposed method can significantly increase the accuracy of estimation of the parameters in stable stimulations (i.e. /da/, /ba/), for both major positive and negative peaks. This improvement is more significant (e.g. up to 2-3 times) for /ba/ stimulus and especially in major positive peaks whereas, in other peaks, the improvements have also occurred but with smaller amounts. However, for unstable stimuli (i.e. /ga/), no significant improvement is achieved. Discussion: Increasing the accuracy performance of the proposed method for detecting the stable stimuli while its performance remains unchanged for detecting unstable stimuli indicates its effectiveness in automated clinical analysis of ABR signals.