A deterministic approach for finding the T onset parameter of flatten T wave in ECG
Identification of the exact nature of flatten T wave in ECG signal is Classification of normal and abnormal T wave episodes especially, regarding Flatten T wave in electrocardiography (ECG) signal is still a complex phenomenon for cardiologists. Identification of Flatten T wave depends on four param...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Institute of Information Science, Academia Sinica
2019
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/24067/ https://jise.iis.sinica.edu.tw/JISESearch/pages/View/PaperView.jsf?keyId=167_2223 |
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| Summary: | Identification of the exact nature of flatten T wave in ECG signal is Classification of normal and abnormal T wave episodes especially, regarding Flatten T wave in electrocardiography (ECG) signal is still a complex phenomenon for cardiologists. Identification of Flatten T wave depends on four parameters; Time duration (T dur ), T onset (T on ), T offset (T off ) and T peak (T pk ) values which play a vital role to identify the exact nature of Flatten T wave. The proposed approach is used to extract the T on value of Flatten T wave with the detection of R peaks and RR intervals. The proposed approach is applied to ten different subjects of Flatten. It is divided into three distinct phases. Firstly, Flatten signals are segmented by lead wise. Secondly, noise filtration is done to identify the peak values and removal of low-frequency components. A third phase computes the R peak values and RR intervals with the help proposed algorithm. By using the R peak value as a fiducial point and considering the last interval of RR interval instead of complete T wave alternans detection algorithm (TWA) for determination the T on parameter of Flatten T wave. The experimental evaluation manifests that efficiency factors are high in rate during the operational investigations (closest to the range of 100%). These efficiency factors have been discussed in the context of accuracy, sensitivity, prediction and error rate. These operation efficiency factors will play a benchmark role in future for calculation the others parameters of Flatten T wave. © 2019 Institute of Information Science. All rights reserved. |
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