Heart Rate and Ischemia Detection Using Wavelet Transform
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 3
Abstract
Electrocardiogram (ECG) is generally used for diagnosis of cardiovascular abnormalities and disorders. An efficient method is implemented towards the detection of heart rate (HR) and ischemic from the ECG signal. The heart rate is calculated using the extracted features of the ECG signal for diagnosing cardiac arrest. The detection of ischemia from a patient’s electrocardiogram (ECG) signal is based on the characteristics of a specific part of the beat called the ST segment which is used to diagnose the heart arrest. Wavelet transforms provides a good learning and detection capabilities which is an efficient tool to deal with uncertainties. Neural network classifier is used for classifying the abnormalities such as arrhythmia, types of ischemia as transmural and non transmural ischemia.
Authors and Affiliations
A. Fancy Nija, M. Kamalanathan
Keywords
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