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针对呼吸信号中包含的心动冲击、动脉搏动等相关噪声,提出了一种基于小波降噪的呼吸信号提取算法。该算法采用db4小波将信号在六个尺度上分解,应用史坦无偏似然估计原理产生自适应阈值对小波系数做阈处理并重构小波系数,处理结果显示噪声信号可被有效剔除。为临床上实现非接触的呼吸监护打下基础。
Aiming at the noise related to heart beat, arterial pulse and other respiration contained in the respiratory signal, a novel respiratory signal extraction algorithm based on wavelet denoising is proposed. This algorithm uses db4 wavelet to decompose the signal on six scales. Using Stein’s principle of unbiased likelihood estimation to generate adaptive threshold, the wavelet coefficients are thresholded and the wavelet coefficients are reconstructed. The results show that the noise signal can be effectively eliminated. Lay the foundation for clinical non-contact respiratory monitoring.