This study demonstrate that machine learning techniques can be effectively used to classify heart diseases using ECG signals. The high accuracy and other performance metrics obtained indicate that these models have the potential to be used in a clinical setting for early diagnosis and treatment of heart diseases.
The overview of Project is given below: Link to Dataset https://data.mendeley.com/datasets/gwbz3fsgp8/2
Pre-processing i).Conversion of ECG images into Gray Scale.
ii Conversion of Gray Scaled images to Binary images
iii Conversion of genearted leads into contours.
iv Scaling and Normalization of obtained contours.
v. Dimensionality Reduction using PCA