Myocardial Ischemia is the most common heart disease. Stress ECG has been effectively used for analysis of the myocardial ischemia than normal ECG because of the reason that ischemic conditions will be dominated in stress conditions. According to the clinically proven facts, after taking a series of exercise, the chance of finding ischemia can rise up to 80%-90%. In ECG, the ST segment detection has close relationship with myocardial ischemia and myocardial infarction. Denoising of the stress ECG has done using filters. The key points of ECG signal like Q, R, S are found out using Pan Tompkins algorithm. Other key points like P, T, Ton, Toff, J, Iso-electric point are also found using window method. The feature of interest is ST segment. Based on R-R interval, heart rate was found out. By considering the age of the individual sub-maximal heart rate is fixed and let the patient to do exercise stress test which lasts until sub-maximal heart rate was reached. The ST segment analysis had been done in time domain as well as in frequency domain. ST trend was analyzed on and after the sub-maximal heart rate. According to the clinically proven facts, for a person having ischemia the ST level shows a depression for about two minutes or more during relaxing stage. The signals from MIT-BIH ST Change Database had been used to verify the algorithm in MATLAB software.
[1]
K.V.L. Narayana,et al.
Wavelet based QRS detection in ECG using MATLAB
,
2011
.
[2]
Rama Valupadasu,et al.
Identification of Cardiac Ischemia Using Spectral Domain Analysis of Electrocardiogram
,
2012,
2012 UKSim 14th International Conference on Computer Modelling and Simulation.
[3]
Yiqiang Chen,et al.
A novel method of diagnosing coronary heart disease by analysing ECG signals combined with motion activity
,
2011,
2011 IEEE International Workshop on Machine Learning for Signal Processing.
[4]
E. Braunwald.
Heart Disease: A Textbook of Cardiovascular Medicine
,
1992,
Annals of Internal Medicine.
[5]
Pablo Laguna,et al.
QRS Slopes for Detection and Characterization of Myocardial Ischemia
,
2008,
IEEE Transactions on Biomedical Engineering.
[6]
Mohammad Saniee Abadeh,et al.
An ensemble PSO-based approach for diagnosis of coronary artery disease
,
2011,
2011 International Symposium on Artificial Intelligence and Signal Processing (AISP).
[7]
L. Gullestad,et al.
Postexercise Ischemia Is Associated With Increased Neuropeptide Y in Patients With Coronary Artery Disease
,
2000,
Circulation.