A Novel Method for Automated Estimation of EffectiveParameters of Complex Auditory Brainstem Response: Adaptive Processing Based on the Correntropy Concept

Objectives: automated auditory brainstem responses (abr) peak detection is a noveltechnique to facilitate the measurement of neural synchrony along the auditory pathway throughthe brainstem. analyzing the location of the peaks in these signals and the time intervalbetween them may be utilized either for analyzing the hearing process or detecting peripheraland central lesions in the human hearing system.methods: in this paper, model-based signal processing is proposed to estimate the effectiveparameters of abr signals. in this process, the biological parameters of the signal are assessedby utilizing a finite impulse response (fir) adaptive filter in which its adaptation procedure isperformed based on the correntropy concept. the proposed method is applied on a set of abrsignals recorded in response to three stimuli of /da/, /ba/, and /ga/, and then its performancesare compared with an existing state-of-the-art technique.results: the results show that the proposed method can significantly increase the accuracyof estimating the parameters in stable stimulations (/da/, /ba/) for major positive and negative peaks. this improvement is more significant (up to 2-3 times) for /ba/ stimulus and especiallyin major positive peaks. however, in other peaks, the improvements also occurred in smalleramounts. however, for unstable stimuli (/ga/), no significant improvement was achieved.discussion: increasing the accuracy performance of the proposed method for detecting thestable stimuli (while its performance remains unchanged) for detecting unstable stimuliindicates its effectiveness in automated clinical analysis of abr signals.