Aplicación Web para la Detección de Patologías en Señales EEG

Abstract

Major depressive disorder (MDD) (also known as clinical depression, major depression, depression or unipolar depressive disorder or as recurrent depression, in the case of repeated episodes) is a mental illness characterized by a invasive and persistent mood accompanied by low self-esteem and a loss of interest or pleasure (anhedonia) in activities that would normally be considered entertaining. Depressed people have a shorter life expectancy than those without depression, in part because depressed patients are at risk of dying by suicide. However, they also have a higher crude death rate from other causes and are more susceptible to medical conditions such as heart disease. Up to 60% of suicides are associated with a mood disorder, such as major depression, and the risk is especially high if the person suffers from hopelessness or has depression and borderline personality disorder. This project aims to be able not only to detect anomalies within the bio-potentials captured by the EEG, both anomalies in this and to catalog the major depression disorder through the use of Artificial Intelligence supported by the libraries offered by the programming language Python for creating neural networks Autoencoders, creating a local server on our PC for HTTP requests an API (Application Programming Interface) for the transfer of information with the client side, and in turn creating a friendly graphical interface with the user created in React.js, who intends to use it, this application is considered to be a support for people suffering from MDD and the specialists who treat it.