Shanghai Jiao Tong University

Yunfeng Hua

Hao Wu

Bei Li

Xueling Wang

Zhiwu Huang

Haoyu Wang

Xu Ding

An automatic test device and method for auditory brainstem response (ABR) collects an ABR dataset at a plurality of sound loudness levels, increases the times of level averaging by iteration based on an adaptive average method, and improves a signal-to-noise ratio until ABR signal detection conditions are met. Signal detection includes determining that the time lag between average curves obtained from the ABR dataset is within a specified range. Iteration is terminated when the ABR signal is detected or a maximum number of iterations is reached. A minimum loudness level required to detect the ABR signal is used as a hearing threshold. An accurate loudness level corresponding to the hearing threshold is obtained by function fitting on the number of iterations used at each loudness level and interpolation. The threshold detection can effectively reduce the number of times that an ABR recording needs to be acquired.

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Shanghai, China

Yunfeng Hua