Paper Title
Denoising of ECG Signals Using Wavelets And Classification Using SVM

Electrocardiogram is the recording of the electrical potential of heart versus time. The analysis of ECG signal has great importance in the detection of cardiac abnormalities. In this paper we have dealt about the removal of noises in ECG signals and arrhythmia classification of the signal.The inputs for our analysis is taken from MIT-BIH database (Massachusetts Institute of Technology Beth Israel Hospital database). The denoising is done through wavelet transform and thresholding. Confirmatory tools such as Poincare plot and Detrended Fluctuation Analysis (DFA) are used to find out the healthiness of the signal. Then Support Vector Machine (SVM) is used to find out what type of arrhythmia is present in the signal. Keywords- Classification, DFAElectrocardiogram, MIT-BIH database, Poincare, SVM , Wavelets.