A Neural Network approach and Wavelet analysis for ECG classification

Ambulatory ECG
DOI: 10.1109/icetech.2016.7569428 Publication Date: 2016-09-19T16:51:45Z
ABSTRACT
ECG is basically the graphical representation of electrical activity cardiac muscles during contraction and release stages. It helps in determination arrhythmias a well manner. Due to this early detection can be done properly. In other words we say that bio-potentials generated by results an signal called Electro-cardiogram (ECG). acts as vital physiological parameter, which being used exclusively know state patients. Feature extraction plays role manual automatic analysis for use specially designed instruments like monitors, Holter tape recorders scanners, ambulatory analyzers. paper study concept pattern recognition done. refers classification data patterns characterizing them into classes predefined set. The falls under application recognition. waveform gives almost all information about heart. feature parameters such spectral entropy, Poincare plot Lyapunov exponent are paper. This also includes artificial neural network classifier identifying abnormalities heart disease.
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