摘要
针对人体脉搏波信号采集过程中,存在由外界条件造成的噪声干扰问题,提出一种结合DD-DT DWT(双密度双树小波变换)和三次样条插值相结合的去噪方法。该方法先运用DD-DT DWT阈值去噪法去除脉搏波信号中的高频噪声,再运用三次样条插值法去除基线漂移的组合滤波算法结构。与小波变换相比,避免了去噪过程中有效信号的丢失,保留了更多的原始波形特征;信号经过降噪后信噪比与均方根误差两项指标都得到了更好的改善。通过仿真实验结果表明,提出的方法能够很好地去除光电容积脉搏波中包含的高频噪声与基线漂移噪声,处理后的信号特征参数提取更简明,为后续的血压模型构建、血氧饱和度计算等提供方便。整体计算简便且适应性强,脉搏波信号质量得到提高,也为可穿戴设备的数据实时分析提供了更好的支撑。
In view of the noise interference caused by external conditions in the process of human pulse wave signal acquisition,a denoising method combining DD-DT DWT(double-density dual-tree discrete wavelet transform)and cubic spline interpolation is proposed.A combined filtering algorithm structure is adopted in the method.The DD-DT DWT threshold denoising method is used to remove high-frequency noise in pulse wave signals,and then the cubic spline interpolation method is used to remove the baseline drift.In comparison with the wavelet transform,this method avoids the loss of effective signals in the denoising process and retains more original waveform features.After noise reduction,the indicators of signal-to-noise ratio(SNR)and root mean square error are both improved better.The results of simulation experiments show that the proposed method can well remove the high-frequency noise and baseline drift noise contained in the photoplethysmography(PPG),and the extracted signal feature parameters after processing are more concise,which is useful for subsequent blood pressure model construction and blood oxygen saturation calculation.The overall calculation is simple and adaptable,and the quality of the pulse wave signals is improved after processing,which also provides better support for the data real-time analysis of wearable devices.
作者
葛君怡
李霞
杨昊
GE Junyi;LI Xia;YANG Hao(College of Information Engineering,China Jiliang University,Hangzhou 310000,China)
出处
《现代电子技术》
2021年第23期39-43,共5页
Modern Electronics Technique
基金
浙江省自然科学基金资助项目(LY18E070005)。
