基于改进阈值的双树复小波眼电信号去噪方法

EOG Signal Denoising Based on Modified Threshold Dual-Tree Complex Wavelet Transform

眼电(EOG,electrooculogram)信号由眼球的运动而产生,通常在采集过程中混入强烈的背景噪声,去噪是对眼电信号作进一步分析和识别的首要步骤。提出将双树复小波变换用于眼电信号的去噪,并采用一种新的阈值估计方法改善统一阈值过度扼杀小波系数的缺点,用均方根误差和信噪比评价眼电信号的去噪效果。结果表明:与传统离散小波变换相比,双树复小波变换既能很好地抑制噪声,又能更好地保留信号的细节,具有较高的实用价值。

Electrooculogram（EOG） signals are generated from the movement of eye,which usually mixed with strong background noise during acquisition process.De-noising is the foremost step in any further analysis or recognition.A new EOG signal denoising method based on dual-tree complex wavelet transform with a modified threshold which improves the performance of VisuShrink for excessive strangling wavelet coefficient is proposed.The denoising performance is evaluated by root-mean-square error and signal to noise ratio.Results demonstrate that the dual-tree complex wavelet transform-based denoising outperforms the conventional discrete wavelet transform both in reducing noise and retaining texture characteristic and it has a high practical value.