ECG Waveform Classification Based on P-QRS-T Wave Recognition

Authors

  • Muzhir Shaban Al-Ani Department of Information Technology – College of Science and Technology - University of Human Development, Sulaymaniyah, Iraq http://orcid.org/0000-0002-7007-8116

DOI:

https://doi.org/10.21928/uhdjst.v2n2y2018.pp7-14

Keywords:

Electrocardiogram; QRS Wave; Feature Extraction; ECG Signal

Abstract

Electrocardiogram (ECG) is a periodic signal reflects the activity of the heart.   ECG waveform is an important issue to define the heart function so it is helpful to recognize the type of heart diseases. ECG graph generate a lot of information that is converted into electrical signal with standard values of amplitude and duration. The main problem raised in this measurement is the mixing between normal and abnormal, in addition some time there are overlapping between the P-QRS-T waveform. This research aims to offer an efficient approach to measure all parts of P-QRS-T waveform in order to give a correct decision of heart functionality. The implemented approach including any steps; preprocessing, baseline process, feature extraction and diagnosis. The obtained result indicated an adequate recognition rate to verify the heart functionality.

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Published

2018-07-25

How to Cite

Al-Ani, M. S. (2018). ECG Waveform Classification Based on P-QRS-T Wave Recognition. UHD Journal of Science and Technology, 2(2), 7–14. https://doi.org/10.21928/uhdjst.v2n2y2018.pp7-14

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Section

Articles