An Improved Cubic Spline Interpolation Method for Removing Electrocardiogram Baseline Drift_Journal of Biomedical Engineering

Authors：

 WANXiangkui ¹ , TANGWenpu ² , ZHANGLai ² , WUMinghu ¹

1. Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan 430068, China;
2. Guangdong Biolight Meditech Co., Ltd, Zhuhai 519015, China;

Corresponding author：

WANXiangkui, Email: ruisin@hotmail.com

Keywords：

cubic spline interpolation; baseline drift; electrocardiogram; fiducial point

DOI：

10.7507/1001-5515.20160040

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

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 1.5 Hz 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 0.242 and 0.13 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.

Citation： WANXiangkui, TANGWenpu, ZHANGLai, WUMinghu. An Improved Cubic Spline Interpolation Method for Removing Electrocardiogram Baseline Drift. Journal of Biomedical Engineering, 2016, 33(2): 227-231. doi: 10.7507/1001-5515.20160040 Copy

1.	夏恒超, 詹永麒.一种新的基于三次样条插值技术的心电图基线漂移消除方法[J].生物医学工程学杂志, 2003, 20(3):524-526, 530.
2.	VAN ALSTÉ J A, SCHILDER T S. Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps[J]. IEEE Trans Biomed Eng, 1985, 32(12):1052-1060.
3.	LIAN Y, YU J-h. A low power linear phase digital FIR filter for wearable ECG device[C]//IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005:7357-7360.
4.	CHOUHAN V S, MEHTA S S. Total removal of baseline drift from ECG signal[C]//International Conference on Computing:Theory and Application.2007:512-515.
5.	万相奎.基于多分辨率分析的ECG基线漂移矫正算法[J].计算机工程与设计, 2008, 29(13):3482-3484.
6.	ALARKA S, ARIJIT B, ABHIJIT L. Application of framelet transform in filtering baseline drift from ECG signals[C]//2nd International Conference on Computer, 2012, 4:862-866.
7.	庞宇, 邓璐, 林金朝, 等.基于形态滤波的心电信号去除基线漂移方法[J].物理学报, 2014, 63(9):428-433.
8.	SHAYEI A, EHSANI S P, SHABANY M. Efficient implementation of real-time ECG derived respiration system using cubic spline interpolation[C]//2013 IEEE international symposium on circuits and systems. Beijing, China, 2013:1083-1086.
9.	席涛, 杨国胜, 汤池, 等.基于自适应滤波的心电图中呼吸信号的提取方法[J].第四军医大学学报, 2005, 26(9):852-854.
10.	田絮资, 杨建, 黄力宇.心电信号去噪的数学形态学滤波器[J].计算机工程与应用, 2012, 48(2):124-126.
11.	MOODY G B, MULDROW W E, MARK R G. A noise stress test for arrhythmia detectors[J]. Computers in Cardiology, 1984, 11:381-384.

1. 夏恒超, 詹永麒.一种新的基于三次样条插值技术的心电图基线漂移消除方法[J].生物医学工程学杂志, 2003, 20(3):524-526, 530.
2. VAN ALSTÉ J A, SCHILDER T S. Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps[J]. IEEE Trans Biomed Eng, 1985, 32(12):1052-1060.
3. LIAN Y, YU J-h. A low power linear phase digital FIR filter for wearable ECG device[C]//IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005:7357-7360.
4. CHOUHAN V S, MEHTA S S. Total removal of baseline drift from ECG signal[C]//International Conference on Computing:Theory and Application.2007:512-515.
5. 万相奎.基于多分辨率分析的ECG基线漂移矫正算法[J].计算机工程与设计, 2008, 29(13):3482-3484.
6. ALARKA S, ARIJIT B, ABHIJIT L. Application of framelet transform in filtering baseline drift from ECG signals[C]//2nd International Conference on Computer, 2012, 4:862-866.
7. 庞宇, 邓璐, 林金朝, 等.基于形态滤波的心电信号去除基线漂移方法[J].物理学报, 2014, 63(9):428-433.
8. SHAYEI A, EHSANI S P, SHABANY M. Efficient implementation of real-time ECG derived respiration system using cubic spline interpolation[C]//2013 IEEE international symposium on circuits and systems. Beijing, China, 2013:1083-1086.
9. 席涛, 杨国胜, 汤池, 等.基于自适应滤波的心电图中呼吸信号的提取方法[J].第四军医大学学报, 2005, 26(9):852-854.
10. 田絮资, 杨建, 黄力宇.心电信号去噪的数学形态学滤波器[J].计算机工程与应用, 2012, 48(2):124-126.
11. MOODY G B, MULDROW W E, MARK R G. A noise stress test for arrhythmia detectors[J]. Computers in Cardiology, 1984, 11:381-384.

Journal of Biomedical Engineering

An Improved Cubic Spline Interpolation Method for Removing Electrocardiogram Baseline Drift

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content