可穿戴心电信号监测中运动伪影消除技术研究

心电图(ECG)是心脏疾病诊断最有效的工具。噪声的去除和Q波、R波、S波的提取是心电信号检测中的两大主题。本文使用Savitzky-Golay滤波器对人体在弯腰、走路、坐下-站起等运动状态下采集的心电信号进行分析，去除信号中的基线漂移和运动伪影，并对滤波后信号的Q波、R波和S波进行检测。通过将本文提出的滤波方式与卡尔曼滤波、小波分解就时间复杂度和功率谱密度两个参数进行对比分析，评估Savitzky-Golay滤波器在心电信号中运动伪影去除的优势。实验结果表明，Savitzky-Golay滤波器能更加有效地适应心电信号的变化，有效地去除心电信号中的噪声，并且最大限度保持心电波形的形状和波峰。 

Research on Motion Artifacts Eliminating for Wearable Electrocardiogram Signal Monitoring

Electrocardiogram(ECG) is the most effective and low cost tool in the diagnosis of heart diseases. The two main research topics about the ECG signal analysis are the noise reduction and the Q wave, R wave, S wave detection. In this paper, the Savitzky-Golay filter is used to removing baseline drift and motion artifacts in motion ECG signals. Here ECG signals are taken from the human body in the bend, walk and sit-stand condition. Then Q wave, R wave and S wave are detected in the filtered signals. We evaluate the advantages of Savitzky-Golay filter in the ECG motion artifact removal by comparing with Kalman filtering and wavelet decomposition. The comparison is done by evaluating different statistical parameters like time complexity and power spectrum density. Experimental results verify that Savitzky-Golay filter can be more effectively adapt to the changes of the ECG signal, more effectively remove the noise without much destroying the shape and the peak of the ECG waveform.