International Journal of Advanced Technology and Engineering Exploration (IJATEE) ISSN (P): 2394-5443 ISSN (O): 2394-7454 Vol - 6, Issue - 50, January 2019
  1. 1
    Google Scholar
Heart beat peak detection using signal filtering in ECG data

J.Rexy , P.Velmani and T.C.Rajakumar

Abstract

Current trends in health industry reveal that the major cause for death ratio increase is due to heart disease. Malfunctioning of heart leads to heart disease and there are multiple forms of heart disease. Electrocardiogram (ECG) is painless and basic test which can detect basic heart related problems. Heart beat variations can be identified by detecting heart beat peaks. Heart beat peak detection plays a vital role for efficient analysis of ECG signals. This paper deals with detecting heart beat peaks in noisy ECG signals which will be helpful to extract required features, to detect heart disease in earlier stage. ECG Signals are taken as primary input to detect the heartbeat peaks for feature extraction purpose. As the noisy EGC signal is normal due to distortion of the original ECG signal because of the various levels of noises, filtering the noisy ECG signal is necessary to detect the heartbeat peaks. Existing digital IIR filters such as Butterworth, Chebyshev Type I, Chebyshev Type II and Elliptic are commonly used for denoising ECG signals to retrieve sharp ECG signal waves. This paper is an attempt to apply the existing methodologies to Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) noise, stress test database ECG signals and perform a quantitative study based on the performance metrics such as specificity, sensitivity, accuracy, mean square error and signal to noise ratio. Both Chebyshev Type II and Elliptic filers reflected poor performance over this dataset. Hence this paper proposes a novel hybrid methodology called ButterChev which is a combined version of Butterworth and Chebyshev Type I filters. The proposed methodology resulted with improved performance metrics and it paves the way for better noise removal and peak detection for the given noisy ECG signal. The implementation process has been carried out using Matlab software environment.

Keyword

ECG signal, Butterworth, Chebyshev Type I, Chebyshev Type II, Elliptic, ButterChev.

Cite this article

J.RexyP.VelmaniT.C.Rajakumar

Refference

[1][1]Chandrakar B, Yadav OP, Chandra VK. A survey of noise removal techniques for ECG signals. International Journal of Advanced Research in Computer and Communication Engineering. 2013; 2(3):1354-7

[2][2]Peterkova A, Stremy M. The raw ECG signal processing and the detection of QRS complex. European modelling symposium 2015 (pp.80-5). IEEE.

[3][3]Magsi H, Sodhro AH, Chachar FA, Abro SA. Analysis of signal noise reduction by using filters. In international conference on computing, mathematics and engineering technologies 2018 (pp. 1-6). IEEE.

[4][4]Singh T, Jain A, Chourasia B. Study and performance analysis of IIR filter for noise diminution in digital signal using MATLAB. International Journal of Computer Science and Mobile Computing. 2017; 6(4):111-7.

[5][5]Acharya A, Lambe RM, Zodge S, Chaudhari J. Implementation of digital filters for ECG analysis. International Journal of Computer Science and Information Technologies. 2014; 5(1):181-3.

[6][6]Pal R. Comparison of the design of FIR and IIR filters for a given Specification and removal of phase distortion from IIR filters. In international conference on advances in computing, communication and control 2017 (pp. 1-3). IEEE.

[7][7]Prabhakar S, Sappal AS. Transition bandwidth analysis of infinite impulse response filters. International Journal of Computer Science & Engineering Technology. 2013; 4(8):1165-70.

[8][8]Hossin M, Sulaiman MN. A review on evaluation metrics for data classification evaluations. International Journal of Data Mining & Knowledge Management Process. 2015; 5(2):1-11.

[9][9]Kim JH, Lee KH, Lee JW, Kim KS. Semi-real-time removal of baseline fluctuations in electrocardiogram (ECG) signals by an infinite impulse response low-pass filter (IIR-LPF). The Journal of Supercomputing. 2018; 74(12):6785-93.

[10][10]Cuomo S, De Pietro G, Farina R, Galletti A, Sannino G. A novel O (n) numerical scheme for ECG signal denoising. Procedia Computer Science. 2015; 51:775-84.

[11][11]Singh N, Ayub S, Saini JP. Design of digital IIR filter for noise reduction in ECG signal. In international conference and computational intelligence and communication networks 2013 (pp. 171-6). IEEE.

[12][12]Li J, Deng G, Wei W, Wang H, Ming Z. Design of a real-time ECG filter for portable mobile medical systems. IEEE Access. 2017; 5:696-704.

[13][13]Gaikwad KM, Chavan MS. Removal of high frequency noise from ECG signal using digital IIR butterworth filter. In IEEE global conference on wireless computing & networking 2014 (pp. 121-4). IEEE.

[14][14]Amiri M, Afzali M, Vahdat BV. Comparison of different electrocardiogram signal power line denoising methods based on SNR improvement. In Iranian conference of biomedical engineering 2012 (pp. 159-62). IEEE.

[15][15]Bhogeshwar SS, Soni MK, Bansal D. Design of simulink model to denoise ECG signal using various IIR & FIR filters. In international conference on reliability optimization and information technology 2014 (pp. 477-83). IEEE.

[16][16]Dhar S, Mukhopadhyay SK, Mitra S, Baig MM, Mitra M. Noise reduction and lossless ECG encoding. In proceedings of the international conference on control, instrumentation, energy and communication 2014 (pp. 210-3). IEEE.

[17][17]Das N, Chakraborty M. Performance analysis of FIR and IIR filters for ECG signal denoising based on SNR. In international conference on research in computational intelligence and communication networks 2017 (pp. 90-7). IEEE.

[18][18]Muppalla V, Suraj NS, Reddy VY, Suman D. Performance evaluation of different denoising techniques for physiological signals. In India council international conference 2017 (pp. 1-6). IEEE.

[19][19]Kumar KS, Yazdanpanah B, Kumar PR. Removal of noise from electrocardiogram using digital FIR and IIR filters with various methods. In international conference on communications and signal processing 2015 (pp. 157-62). IEEE.

[20][20]Bhateja V, Urooj S, Verma R, Mehrotra R. A novel approach for suppression of power line interference and impulse noise in ECG signals. In IMPACT-2013 (pp. 103-7). IEEE.

[21][21]Sandhu M, Kaur S, Kaur J. A study on design and implementation of butterworth, chebyshev and elliptic filter with matlab. International Journal of Emerging Technologies in Engineering Research. 2016; 4(6):111-4.

[22][22]Bindu CH. Performance analysis of demising of ECG signals in time and frequency domain. In computational intelligence and big data analytics 2019 (pp. 81-95). Springer, Singapore.

[23][23]Ahmad AS, Matti MS, ALhabib OA, Shaikhow S. Denoising of arrhythmia ECG signals. International Journal of Medical Research and Health Sciences. 2018; 7(3):83-93.

[24][24]Saini A, Kumar N, Raj A, Jain S. Performance analysis of cascaded denoising block for ECG signal analysis using different filters. In international conference on “computing for sustainable global development. 2018 (pp. 2251-6).

[25][25]Latif R, Jenkal W, Toumanari A, Hatim A. Electrocardiogram signal denoising using a hybrid technique. World Academy of Science, Engineering and Technology, International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering. 2017; 11(3):256-9.

[26][26]Bhutada SN, Shinde AV, Thote CG. Efficient method for ECG denoising–survey. International Journal of Advanced Research in Electronics and Communication Engineering. 2017; 6(4):318-21.

[27][27]Rishabhkumar MN, Parashar P. Design and implementation of butterworth, chebyshev-I filters for digital signal analysis. International Research Journal of Engineering and Technology (IRJET).2018; 5(3):2707-9.

[28][28]Kumar A, Mamta. Comparison of different types of IIR filters. International Journal of Advanced Research in Electronics and Communication Engineering. 2016; 5(2):393-402.

[29][29]Saini MS, Kaur K. Performance analysis of IIR filter design by using butterworth, chebyshev and cauer. International Journal of Advanced Engineering Research and Science. 2015; 2(3):29-36.

[30][30]Yazdanpanah B, Raju KS. Design and comparison of digital IIR filters for reduction of artifacts from electrocardiogram waveform. International Journal of Engineering Research and General Science. 2014; 2(6):982-8.

[31][31]Chavan MS, Agarwala RA, Uplane MD. Comparative study of chebyshev i and chebyshev II filter used for noise reduction in ECG signal. International Journal of Circuits, Systems and Signal Processing. 2008; 2(1):1-17.

[32][32]Jagtap SK, Uplane MD. A real time approach: ECG noise reduction in chebyshev type II digital filter. International Journal of Computer Applications. 2012; 49(9):52-9.

[33][33]Chavan MS, Agarwala RA, Uplane MD. Digital elliptic filter application for noise reduction in ECG signal. WSEAS international conference on electronics, control and signal processing, Miami, Florida, USA 2005(pp.58-63).