基于希尔伯特-黄变换的AEP去噪方法

AEP Noise Removal Method Based on Hilbert-Huang Transform

在高刺激率模式下,采用去卷积方法提取暂态的听觉诱发电位存在噪声敏感的问题。为此,提出一种结合希尔伯特-黄变换(HHT)与总体相关的去噪方法。利用HHT方法提取有用信号,通过总体相关方法区分混叠在同一频率段的信号和噪声,获得相关性强的成分。实验结果表明,该方法能在不增加刺激个数的情况下,使得平均信号的信噪比提高约4倍,且不需要信号的先验知识和人为干预,便于应用。

This paper presents a method based on a combination of Hilbert-Huang Transform（HHT） and Ensemble Correlation（EC） to address the noise sensitivity problem of retrieving transient Auditory Evoked Potential（AEP） using Continuous Loop Averaging Deconvolution（CLAD） technique.The HHT decomposes the Electroencephalogram（EEG） signal into different frequent bands for the selection of components of interest.Then EC is introduced to measure the consistence of the corresponding components so that the signal enhancement or attenuation can be implemented accordingly.Results show that the method can effectively enhance the SNR of AEP by a factor of four without requiring a priori information on the signal and induced noise.