EEG Signal Denoising based on Wavelet Transform using Xilinx System Generator - 2018


Low amplitude EEG signal are simply affected by varied noise sources. This work presents de-noising methods based on the combination of stationary wavelet remodel (SWT), universal threshold, statistical threshold and Discrete Wavelet Transform (DWT) with symlet, haar, coif, and bior4.4 wavelets. The results show important improvement in performance parameter like Signal to Artifacts ratio (SAR), Correlation Coefficient (CC) and Normalized Mean Squared error (NMSE). Simulink has been used to model DWT based de noising of EEG signal implementable on FPGA with Xilinx System Generator.

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