Aplicación de técnicas de aprendizaje de máquina para facilitar la comunicación en pacientes con neuropatía periférica utilizando señales eeg y visión computacional : Modelo de redes convolucionales basadas en rostros para la detección de movimientos en videos aplicando el seguimiento de las pupilas.

Abstract

Technology advances and so do people's diseases, in this case neuropathy is a disease which does not allow good communication, because technology can help these people to improve their quality of life, in this case artificial intelligence is applied. There are several ways to achieve communication, in this case the gaze and blinks are used for the selection of an action, this facilitates the way in which such people could communicate, for this several architectures were implemented and tests were performed for the validation of such models, the tests were performed in a controlled environment with software similar to the dataset to obtain better results. For this reason a model was implemented with which the automatic recognition of events can be achieved, extracting specific characteristics of a person, for this machine learning techniques have been applied in order to implement a model that is able to work under certain conditions and also using computer vision.