Bradycardia Detection using ECG Signal Processing and MATLAB

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  •   Ledisi Giok Kabari

  •   Ugochukwu C. Onwuka

Abstract

Electrocardiogram is the record of electrical activity of heart. ECG is a test to detect and study normal rhythmic activity of the heart. Signal processing are very often used methods in a biomedical engineering research. This paper presents Bradycardia detection by utilization of digital signal filtering on electrocardiogram (ECG) using MATLAB. MATLAB was used to analyze and process ECG dataset gotten from Physionet online database with focus on R-R peaks to calculate the heartbeat, by applying high pass filtering and squaring the signal. The results obtained using MATLAB for ECG analysis and detection of arrhythmia is very fast and useful.


Keywords: Bradycardia, Biomedical Engineering, Heartbeat, MATLAB, Signal Processing

References

I. K. Rajni(December, 2013), Electrocardiogram Signal Analysis -An Overview, International Journal of Computer Applications, 84(7), pp 0975 –8887.

I. Kaur, R. Rajni and G. Sikri(Mar, 2014), Denoising of ECG Signal with Different Wavelets, International Journal of Engineering Trends and Technology (IJETT), 9 (13), pp 658-661.

I. Kaur, R. Rajni and A. Marwaha(2016), ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform, springer,97(4), pp 499-507.

P. Tirumala Rao, S. Koteswarao Rao2, G. Manikanta1 and S. Ravi Kumar1 (2016), Distinguishing Normal and Abnormal ECG Signal, Indian Journal of Science and Technology, [Online] 9(10), pp. 0974-5645

M. Al-Ani (July, 2018), Electrocardiogram Waveform Classification Based on P-QRS-T Wave Recognition, UHD Journal of Science and Technology.

R. B. Ghongade and A. A. Ghatol(2009), Deciding optimal number of exemplars for designing an ECG pattern classiier using mlp. Indian Journal of Science and Technology. 2(4), pp1–5.

Verywellhealth (October, 2018), What Is Bradycardia? Available online at https://www.verywellhealth.com/sinus-bradycardia-1746253

Physionet (October, 2018) 200.dat, MIT-BIH Arrhythmia Database Available online at https://physionet.org/physiobank/database/mitdb/

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How to Cite
[1]
Kabari, L. and Onwuka, U. 2019. Bradycardia Detection using ECG Signal Processing and MATLAB. European Journal of Engineering Research and Science. 4, 3 (Mar. 2019), 163-165. DOI:https://doi.org/10.24018/ejers.2019.4.3.1207.