Open AccessAn enhanced threshold free-method for T-Wave detection in noisy environment
Author(s) -
Mohammed O. Sheikh,
Adnan Abdullah Zain,
Majdi Marai
Publication year - 2021
Publication title -
mağallaẗ ğāmi'aẗ 'adan li-l-'ulūm al-ṭabīyyaẗ wa-al-taṭbīqiyyaẗ
Language(s) - English
Resource type - Journals
eISSN - 2788-9327
pISSN - 1606-8947
DOI - 10.47372/uajnas.2021.n1.a09
Subject(s) - filter (signal processing) , matlab , sensitivity (control systems) , computer science , pattern recognition (psychology) , window (computing) , band stop filter , medical diagnosis , sudden cardiac death , artificial intelligence , clinical practice , p wave , low pass filter , cardiology , electronic engineering , computer vision , medicine , engineering , pathology , atrial fibrillation , operating system , family medicine
The electrocardiogram (ECG) signals provide information on the heart rate where it provides evidence to support the diagnoses of cardiac diseases and arrhythmias. Currently ,T-wave has been used to forecast Sudden Cardiac Death (SCD). T-wave recognition is an excellent indicator in the analysis and interpretation of cardiac arrhythmia. Based on this aspect, it is necessary to develop an accurate technique for the detection of these waves. The main aim of this current study is to develop a new threshold-free method for the detection of T wave peak in an (ECG), which was characterized by a threshold free detection of T peak with a special moving window for T wave (and can be used for P wave) between each two RR peaks. A Band pass filter and a notch filter are used to enhance the detection of these required peaks. This algorithm is implemented using MATLAB tools. The database used in this work is downloaded from MIT-BIH Arrhythmia(Lead II). The method is validated using 40 recorded data. The obtained average sensitivity and average positive predictivity of the detection method are 98.4% and 99.0% respectively.