【摘要】 脉搏波可被看作是心脏血管和其他器官在人体体表的表达。脉搏波波形形状和局部特征点承载了大量的人体体征信息。对脉搏波信号进行高效的预处理去噪,对后续人体疾病诊断和健康检测具有重要意义。鉴于传统小波硬阈值除噪方法会引入伪吉布斯现象,软阈值除噪法会对信号产生过度平滑的缺陷,文章采用基于平移时不变小波变换的新阈值除噪方法。实验结果表明,与传统小波去噪方法比较该方法具有更高的信噪比和更低的均方根误差,能够有效抑制伪吉布斯现象。更多还原

【Abstract】 Pulse waves can be thought of as the expression of cardiovascular and other organs in the human body. Pulse wave shape and local feature points carry a large number of human body signs information. The efficient pretreatment and denoising for pulse wave signals is of great significance to the subsequent diagnosis and health detection of human diseases. In view of the traditional wavelet denoising method will introduce pseudo-Gibbs phenomenon,and the soft threshold denoising method will produce over-smooth signal defects,this paper uses a new method of threshold-based wavelet transform invariant wavelet transform. Experimental results show that this method has higher SNR and lower root mean square error compared with the traditional wavelet denoising method,and can effectively suppress the pseudo-Gibbs phenomenon.更多还原