Median averaging of auditory brain stem responses.

Abstract

The primary aim of this study is to demonstrate the feasibility of acquiring auditory evoked potentials (AEPs) by median averaging and study its performance under various recording conditions. The auditory brain stem response (ABR) was used as the AEP of choice because it has the poorest signal to noise ratio (SNR) with inherent high susceptibility to extraneous noise. Secondary aim is to evaluate the characteristics of the median ABRs in comparison with the conventional mean averaged ABRs. Single sweep responses to clicks obtained from four subjects at 5 dB steps were saved in hard disk and used for off-line mean and median averaging. The characteristics of the median averaging technique were investigated by manipulating the averaging procedure using the same set of single sweep recordings and comparing them with the mean averaged responses. The effects of analog to digital input resolution (bit size) was simulated computationally by increasing quantization. The results showed that AEPs with low SNRs such as the ABR can be successfully acquired using median averaging with about the same number of sweeps as was required for mean averaging, provided the EEG signal is digitized with a high number of bits. The resulting waveform generally contained more identifiable waves than the corresponding mean average and had a high-frequency noise superimposed on it. This high-frequency noise was successfully filtered out using a digital, running mean smoothing filter. The median average showed an advantage over the mean average when occasional artifacts were recorded. The results showed that ABRs can be acquired successfully by median averaging provided EEG is digitized with high bit size. Compared with conventional mean averaging, median averaging is less sensitive to infrequent, externally and internally generated noise that plagues conventional techniques and may help improve wave identification.