• Pranali Gopichand Tembhurne
• Dr.Jayant Karanjekar
• Dr. Tryambak Hiwarkar

one of the major causes of human deaths worldwide is cardiovascular diseases (CVD). The increasing threats of CVD can be early detected with various medical tests including electrocardiogram (ECG), and now newly formed CVD tests like 2D Echo, Stress test etc. With the help of this signal, early detection of CVD is possible and it will help the medical system to take preventive action to reduce the cause of CVD for human life. All these signals coming from various medical equipment may be monotonous, time- consuming and stressful to inspect all this manually. To overcome this limitation of manual ECG signal analysis, this research work uses a novel discrete wavelet transform (DWT) method combined with nonlinear features for automated characterization of CVDs. ECG signals of normal, dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM) and myocardial infarction (MI) are subjected to five levels of DWT. The relative wavelet of four nonlinear features such as fuzzy entropy, sample entropy, fractal dimension, and signal energy is extracted from the DWT coefficients. These features are fed to sequential forward selection (SFS) technique and then ranked using the relief method. Our proposed methodology is inclusive ofmultiple CVD devices signal which helps us to increase the accuracy of the data and give the right prediction to hospital as well as individual human life.

CVD, ECG, Discrete Wavelet Transform, Myocardial infarction, Dilated Cardiomyopathy, Hypertrophic cardiomyopathy

"To Identify and Predict Cardiovascular Disease Using ECG signals", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.f286-f288, May-2022, Available :http://www.jetir.org/papers/JETIR2205646.pdf

"To Identify and Predict Cardiovascular Disease Using ECG signals", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppf286-f288, May-2022, Available at : http://www.jetir.org/papers/JETIR2205646.pdf