Abstract

The aim of this study was to investigate methods to improve signal-to-noise ratio (SNR) of extratympanic electrocochleography (ET-ECOG); a low SNR electrophysiological measurement technique. The current standard for ET-ECOG involves acquiring and uniform averaging ∼1000 evoked responses to reveal the signal of interest. Weighted averaging is commonly employed to enhance SNR of repetitive signals in the presence of a nonstationary noise, yet its efficacy in ET-ECOG has not been explored to date, which was the focus of this study. Conventional techniques used to compute signal statistics required for weighted averaging were found to be ineffective for ET-ECOG due to low SNR; therefore, a modified correlation coefficient-based approach was derived to quantify the "signal" component. Several variants of weighted averaging schemes were implemented and evaluated on 54 ECOG recordings obtained from seven healthy volunteers. The best weighted averaging scheme provided a 17% (p < 0.05) SNR increase [signal amplitude to standard deviation (STD) of the noise ratio] compared to uniform averaging, and further improved to 22% (p < 0.05) when variance of the noise was incorporated as a cost factor. The implemented weighted averaging schemes were robust and effective for variants of ET-ECOG recording protocols investigated. Weighted averaging improved SNR of low amplitude ET-ECOG recordings in the presence of nonstationary noise. SNR improvements for ECOG have significant benefits in clinical applications; the variability associated with biofeatures extracted can be reduced, and may lead to shorter recordings. Methods described in this study can easily be incorporated in other low SNR repetitive electrophysiological measurement techniques.

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