Removal of Baseline Wander Noise from Electrocardiogram (ECG) using Fifth-order Spline Interpolation
|Published in:||Issue 2, (Vol. 10) / 2016|
|Author(s):||OJO John A., ADETOYI Temilade B., ADENIRAN Solomon A.|
|Abstract.||Baseline wandering can mask some importantfeatures of the Electrocardiogram (ECG) signal hence it isdesirable to remove this noise for proper analysis and display ofthe ECG signal. This paper presents the implementation and evaluation of spline interpolation and linear phase FIR filtering methods to remove this noise. Spline interpolation method requires the QRS waves to be first detected and fifth-order (quintic) interpolation technique applied to determine the smoothest curve joining several QRS points. Filtering of the ECG baseline wander was performed by using the difference between the estimated baseline wander and the noisy ECG signal. ECG signals from the MIT-BIT arrhythmia database was used to test the system, while the technique was implemented in MATLAB. The performance of the system was evaluated using Average Power (AP) after filtering, Mean Square Error (MSE) and the Signal to Noise Ratio (SNR). The quintic spline interpolation gave the best performance in terms of AP, MSE and SNR when compared with linear phase filtering and cubic (3rd-order) spline interpolation methods.|
|Keywords:||Baseline Wander, Electrocardiogram, Electrocardiography, Quintic Spline Interpolation|
1. J. Allen, J. Anderson, G.J. Dempsey and A.A.J. Adgey (1994), "Efficient Baseline Wander Removal for Feature Analysis of Electrocardiographic Body Surface Maps", IEEE proceedings of Engineering in Medicine and Biology Society, 2, 1316-1317.
2. Z. Barati and A. Ayatollahi (2006), "Baseline Wandering Removal by Using Independent Component Analysis to Single-Channel ECG data", IEEE conference on Biomedical and Pharmaceutical Engineering, 152-156.
3. C.R. Meyer and H.N. Keiser (2006), Electrocardiogram baseline estimation and removal using cubic splines and space-state computation techniques, in Computers and biological research (1977), 10 (5), 459-470. F.A. Davis (ed), "ECG_NOTES", 2005.
4. A.J. Moss and S. Stern (1996), Noninvasive electro cardiolog, Clinical aspects of Holter monitoring Ser. Frontiers in cardiology. W.B. Saunders.
5. MIT-BIH arrhythmia database. [Online]. Available at http://www.physionet.org/physiobank/database/mitdb/.
6. N-Pan, I. V-Mang, U. M-Peng and H. P-Sio (2007), Accurate Removal of Baseline Wander in ECG Using Empirical Mode Decomposition, IEEE International Conference on Functional Biomedical Imaging. pp 177-180.
7. S. Priyadarshini (2010), "ECG Signal Analysis: Enhancement and R-Peak Detection" An Unpublished master's thesis submitted to National Institute of Technology, Rourkela (Deemed University).
8. J. Pan and W.J. Tompkins (1985), A Real-Time QRS Detection Algorithm, IEEE Transactions on Biomedical Engineering, 32 (3), pp 230-236.
|Back to the journal content|
This article is licensed under a
Creative Commons Attribution-ShareAlike 4.0 International License.