Welcome to Francis Academic Press

International Journal of Frontiers in Engineering Technology, 2022, 4(5); doi: 10.25236/IJFET.2022.040508.

Filter design for ECG signal processing


Haoren Xu1, Boning An2, Xie He3

Corresponding Author:
Xie He

1School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun, Jilin Province, China

2SWJTU-Leeds Joint School, Southwest Jiaotong University, Chengdu, Sichuan Province, China

3University of Glasgow, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China 


Digital filters, as one of the most essential tools for signal processing, are often used in ECG signal processing. The hardware implementation of conventional digital filters relies on a hybrid device composed of a digital multiplier, an adder, and a delay unit. However, it has characteristics of a large amount of calculation, complex structure, and high overhead. With the development of computer technology, software implementation of signal processing and filter designing has been increasingly used. As a typical physiological signal, an ECG signal is characterized by a weak signal, complex noise, broad frequency spectrum, and little data sampling. The ECG filter designed by software can effectively weaken the useless noise in ECG signals, helping medical personnel obtain relevant information on patients’ symptoms and realize the diagnosis of diseases.


signal processing, digital filter, software design, ECG filtering, disease diagnosis

Cite This Paper

Haoren Xu, Boning An, Xie He. Filter design for ECG signal processing. International Journal of Frontiers in Engineering Technology (2022), Vol. 4, Issue 5: 42-51. https://doi.org/10.25236/IJFET.2022.040508.


[1] Cheng Xie-Feng, Li Yun-Yi, Gao Pei-Xi, et al. A method for source component acquisition of ECG signals [J]. Journal of Nanjing University of Posts and Telecommunications: Natural Science Edition, 2018, 38( 1) : 54-59.

[2] Hu X, Wang W. Wavelet transform-based ECG localization. Biomedical and Clinical. 4(6), 181-184, 2002.

[3] Huang J, Pei WJ. Fuzzy filtering based on estimated entropy [J]. Data Acquisition and Dissociation. 13(2), 140-142, 1998

[4] ECG signal processing based on MATLAB [EB / OL], Research, December 19, 2017 Available at: https://blog.csdn.net/zhaomengszu/article/details/78842613.

[5] Li G-L, Hu C-G, Zhang J. Adaptive digital filter design in ECG signal processing [J] . Computer Technology and Application Design. 290-294, 2004

[6] Citation format: XU Chun-Dong, ZHOU Jing, YING Dong-Wen, et al. Optimization of MFCC feature vector extraction method for ECG signals [J]. Signal Processing, 2019, 35 (3): 410-418. doi: 10.16798/j.issn.1003-0530.2019.03.012.

[7] Wang RZ,Li LL,Feng YANER. FIR digital filter design based on Kaiser window function[J]. Fujian Computer,2012,28(03):21-22+35.

[8] Gu Xuan,Zhang Wei, Liu Donghua, Liang Fu'e, Lv Shanshan. Elimination of baseline drift of ECG signal based on IIR digital filter [J]. Information Technology and Informatization, 2021(12):177-179.

[9] Huang Bo. Design and simulation implementation of Butterworth digital filter [J]. Henan Science and Technology, 2021,40(36):10-12.

[10] Li G-L, Hu C-G, Zhang J. Adaptive digital filter design in heart tone signal processing [C]//. Proceedings of the 13th National Conference on Computer Aided Design and Graphics (CAD/CG). ,2004:303-306.