Heart Function Monitoring, Prediction and Prevention of Heart Attacks
Date: December 2017
Skills: Java, R-Programming, Python, MySql.
We have developed an efficient method to acquire the clinical and ECG data, so as to train the Artificial Neural Network to accurately diagnose the heart and predict abnormalities if any. The overall process can be categorized into three steps. Firstly, we acquire the ECG of the patient by standard 3 lead pre jelled electrodes. The acquired ECG is then processed, amplified and filtered to remove any noise captured during the acquisition stage. Finally we use these two data’s i.e. ECG and clinical data to train the neural network for classifying the heart disease and to predict abnormalities in the heart or it’s functioning.
Deep Learing Neural Network