Abstract: 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.

Abstract: The present disclosure relates to the technical field of image fusion, and provides a method and apparatus for three-dimensional dynamic tracking, an electronic device, and a storage medium. The method includes: acquiring facial dynamic data, three-dimensional tooth data, and face template data; registering the acquired facial dynamic data, three-dimensional tooth data, and face template data to a preset coordinate system to obtain initial point cloud data; fusing initial depth point cloud data to acquire a contour plane, and acquiring target depth point cloud data; back-projecting the target depth point cloud data to initial texture data, and acquiring target texture data corresponding to the facial dynamic data after back-projection; optimizing initial face template point cloud data to acquire target face template point cloud data fitting the target face template point cloud data and a tooth region identified by the initial texture data with initial three-dimensional tooth data in a fitting region.

Abstract: 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.