TITLE:
Electrocardiogram Feature Extraction and Pattern Recognition Using a Novel Windowing Algorithm
AUTHORS:
Muhammad Umer, Bilal Ahmed Bhatti, Muhammad Hammad Tariq, Muhammad Zia-ul-Hassan, Muhammad Yaqub Khan, Tahir Zaidi
KEYWORDS:
Electrocardiogram, PLI, Windowing, Arrhythmia, Intervals, Cardiac, PQRST
JOURNAL NAME:
Advances in Bioscience and Biotechnology,
Vol.5 No.11,
October
17,
2014
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.