Analysis of ECG Signals for the Diagnosis of Pathologies in Real Time using Computational Algorithms

This project consists of creating a low-cost ECG device capable of providing a valid self-diagnosis of the heart condition of users who live in remote areas of the city and do not have a specialist who can guide and help them to prevent possible future cardiac diseases, for this it is necessary and essential the database of signals obtained from different types of patients and places of the country which is normalized, filtered with wavelet and sent to the neural network code in Python so that you can learn and have a high degree of certainty in the diagnosis. In addition, all of this is monitored remotely by facilitating the sending of data to a city hospital for verification.