Calibration System For Brainstem Auditory Evoked Potential Instrument Based On Wavelet Denoising

With NI-PXI device as the core, the system uses the host matching high precision acquisition card made by the NI company, insteading of the original signal generator, amplifier, filter, frequency meter and voltage meter, while reducing instruments, to ensure the accuracy and effectiveness of signals. At the same time, the PXI host LabVIEW program can manage auxiliary equipment of the system, reducing artificial participation, improving the automation of the calibration system process.In terms of software, the system uses LabVIEW graphical programming language, introducing the principle of modular design. The software framework is divided into the underlying driver module, calibration module and system modules and so on. The underlying driving module including the hardware management, data acquisition and processing, filtering algorithm, database management, and other functions, is the basis of the calibration system. And calibration module is the main executor system, defining the calibration process, each test sound stimulus calibration and EEG acquisition and calibration of two calibration parts requirements. System modules, including user interface layer, control each brainstem evoked potentiometer of calibration, calibration system is the center of the interaction with the outside world. And in each level of software framework, each independent functions are encapsulated as child module, realizes the software requirements of low coupling.In the brainstem evoked potentiometer calibration system implementation, accessing to the brain stem evoked potentiometer sound stimulation should be an important issue. In stimulating calibration part, due to the sound stimulus size0db and120db, the dynamic range change is big. And the signal which at0db～40db margin is very small will be submerged in the noise. This system is to design a set of weak signal detection platform, based on the wavelet threshold denoising algorithm, extracted from the noise of the large amplitude faint useful signal. The whole platform is mainly divided into three parts. First respectively measured signals in noisy environment and quiet environment, no noise signal and noise signal, and then noise signal input to the system of weak signal detection, wavelet denoising, the calibration parameters of the three signals extracted were compared. Experiments show that the algorithm has a good denoising effect.Calibration of the system can complete the brainstem evoked potentiometer, simple operation, to improve the calibration efficiency, reduce the requirement for test personnel. Verification results of the experimental results show that the calibration system is accurate and effective which can effectively eliminate the noise by wavelet denoising algorithm. It can be used in the brainstem evoked potentiometers’daily checks.