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Electrocardiography (ECG) is a widely used noninvasive clinical tool for the diagnosis of cardiovascular disease. However, the accuracy of ECG analysis significantly affect the diagnostic error rate of cardiovascular diseases. Therefore, in recent year, many Neural Network (NN)-based approaches were proposed to automatically analyze the ECG signal. However, these methods suffer from long computing...
One of the most common cardiovascular diseases is Myocardial Ischemia (MI). The aim of this study is improving the diagnosis level of Ischemic Beat detection from ECG signals which is important in ischemic episode detection process. This improvement is based on appropriate feature extraction via Multi resolution Wavelet analysis and proper classifier selection. The approach starts with signal preprocessing,...
Obstructive sleep apnea (OSA) is a common sleeping disorder resulting in the temporary blockage of the upper airways that can lead to increased hypertension and risk to other cardiovascular diseases. Most sleep apnea cases currently remain undiagnosed due to cost and resource limitations of overnight polysomnography at sleep laboratories. In this project, we demonstrate a Simulink-based, modular and...
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