Abstract
This paper presents a Novel Windowing Algorithm for Electrocardiogram Feature Extraction and Pattern Recognition. The work presented here deals with a simple and efficient way of detecting ECG features that are P, Q, R, S and T waves. Windowing method is used to select these waves. Windows are based on varying R-R intervals. It has been tested on ECG simulator data and also on different records of the MIT-BIH arrhythmia database, producing satisfactory results. ECG timing intervals are also required for monitoring the cardiac condition of patients. Hence after feature detections ECG timing intervals like the PR interval, QRS duration, the QT interval, the QT corrected interval and Vent Rate are efficiently calculated using proposed Formulae.
Highlights
An electrocardiogram is a graph depicting the electrical activity generated by the depolarization and repolarization of atria and ventricles
Most of the clinically useful information in an ECG signal is present in the intervals and amplitudes defined by its features
A novel algorithm based on the windowing technique is discussed in this paper which is used for high precision ECG feature extraction and pattern recognition
Summary
An electrocardiogram is a graph depicting the electrical activity generated by the depolarization and repolarization of atria and ventricles. ECG signal analysis is vital for making the data useful in the diagnosis of heart diseases. The development of efficient ECG feature extraction algorithms is of great value and importance. An ECG feature extraction algorithm is helpful in the detection of cardiac problems known. How to cite this paper: Umer, M., et al (2014) Electrocardiogram Feature Extraction and Pattern Recognition Using a Novel Windowing Algorithm. A novel algorithm based on the windowing technique is discussed in this paper which is used for high precision ECG feature extraction and pattern recognition. It explains the different steps involved in implementing the windowing algorithm.
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