Published Paper Details:

The concept of pattern recognition relates to the categorization of data patterns and the differentiation of these patterns into a set of categories that have been predetermined. This is the analysis. Pattern recognition is put to use in the interpretation of ECG signals. The waveform that is formed by the ECG signal provides practically all of the information that is needed on the activity of the heart. It is a bioelectrical signal that is used in the process of documenting the electrical activity of the heart in relation to the passage of time. In order to properly diagnose cardiac disorders and choose the most effective course of therapy for a patient, early and accurate diagnosis is essential. ECG signals are the parameter that is utilised for the identification of cardiac disorders, and the majority of the data originates from the databases maintained by PhysioDataNet and MIT-BIH. In this research, the spectral entropy, Poincare plot, and Lyapunov exponent are some of the ECG signal feature extraction characteristics that are put under the microscope. Additionally, this study utilises an artificial neural network as a classifier for the purpose of determining the anomalies associated with cardiac disease.