| Autor: |
LOKESH S., UDHAYAKUMAR G. |
| Předmět: |
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| Zdroj: |
i-Manager's Journal on Digital Signal Processing; Apr-Jun2019, Vol. 7 Issue 2, p10-14, 5p |
| Abstrakt: |
Electrocardiogram (ECG) is the most vital and widely used methodology to check the cardiovascular diseases. For identifying arrhythmia classification, it needs large storage space and intensive manual effort. The conventional technique of visual analysis to examine the ECG signals by doctors or physicians is not effective and time consuming. In this work, an attempt has been made towards the development of an automated system for investigation of QRS wave in ECG signals using Entropy and Edge detection. The Peak detection process starts only when the enhanced signal exceeds the preset average threshold. Conventional ECG signals are used from MIT/BIH arrhythmia database for this study. The ECG signals are processed using edge based detection and related to Pan-Tompkins algorithm for extracting the QRS features using Entropy threshold of edge detection operators. The results show that the proposed system has a sensitivity of 99.2% and accuracy values of 98.11% and a positive prediction of 98.9% using Prewitt based edge detection. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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