基于DSP Builder的脑电信号小波处理

Wavelet processing on EEG signal based on DSP Builder

针对脑电信号非平稳性特点,利用小波变换对采集到的脑电信号进行滤波处理。然而小波变换巨大的计算量限制其在高速实时信号处理领域的应用,FPGA器件兼具并/串行工作方式,具有较高的并行计算能力,在现场数字信号处理领域具有较强的实时性。提出基于FPGA的小波变换系统设计方法,首先利用DB2小波对脑电信号按Mallat算法进行分解,然后采用小波重构算法去噪。试验结果表明,运用小波分解重构算法,可以对脑电信号进行实时滤波。

Aiming at the non-stationary feature of EEG signal,this paper uses the wavelet transform to denoise the EEG signal.However,since the complex computation of wavelet transform,it is hardly used in high real-time fields.While the FPGA devices can work in parallel model and serial model,and they have the high-speed computation,so it is more effi- cient in real-time fields. So a method of design wavelet transform system based on FPGA is presented ,firstly ,based on the Mallat algorithm,the EEG signal is decomposed by DB2 wavelet,secondly, the wavelet reconstruction algorithm is used to remove the noise.The experimental results show that the wavelet decomposition and reconstruction algorithm is proved to be effective for real-time denoising EEG signal.