改进的三次样条插值心电基线漂移滤波法

An Improved Cubic Spline Interpolation Method for Removing Electrocardiogram Baseline Drift

基准点选择对三次样条插值法去噪的效果有重要影响。本文针对通常的三次样条插值滤波方法,提出一种改进的心电(ECG)信号滤波算法,能适应更宽范围的基线噪声频率分布。算法通过对原始ECG信号求一阶导数,得到每一个心拍周期内的最大和最小值点,其对应的位置作为基准点的位置。然后对原始ECG信号通过截止频率为1.5Hz的高通滤波器,将滤波前后基准点所对应信号幅值的差值作为基准点的幅度。对这些基准点进行三次样条插值曲线拟合,所得拟合曲线为基线漂移曲线。改进算法与原单点法相比,在模拟两种基线漂移情况下,改进样条差值的拟合基线漂移曲线对模拟基线漂移的相关系数分别提高了0.242和0.13;真实基线漂移的情况下,多个临床数据实验显示改进样条差值法平均相关系数达到0.972。

The selection of fiducial points has an important effect on electrocardiogram（ECG）denoise with cubic spline interpolation.An improved cubic spline interpolation algorithm for suppressing ECG baseline drift is presented in this paper.Firstly the first order derivative of original ECG signal is calculated,and the maximum and minimum points of each beat are obtained,which are treated as the position of fiducial points.And then the original ECG is fed into a high pass filter with 1.5Hz cutoff frequency.The difference between the original and the filtered ECG at the fiducial points is taken as the amplitude of the fiducial points.Then cubic spline interpolation curve fitting is used to the fiducial points,and the fitting curve is the baseline drift curve.For the two simulated case test,the correlation coefficients between the fitting curve by the presented algorithm and the simulated curve were increased by 0.242and0.13 compared with that from traditional cubic spline interpolation algorithm.And for the case of clinical baseline drift data,the average correlation coefficient from the presented algorithm achieved 0.972.