Implementation of a brain-machine interface for controlling a wheelchair

• Autores: Alvarado Diaz, Witman, Meneses Claudio, Brian, Roman Gonzalez, Avid
• Formato: objeto de conferencia
• Fecha de Publicación: 2017
• Institución: Universidad de Ciencias y Humanidades
• Repositorio: UCH-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.uch.edu.pe:uch/356
• Enlace del recurso: http://repositorio.uch.edu.pe/handle/uch/356; https://ieeexplore.ieee.org/document/8229668; http://dx.doi.org/10.1109/CHILECON.2017.8229668
• Nivel de acceso: acceso embargado
• Materia: Computer control systems; Deep learning; Electroencephalography; MATLAB; Medical computing; Neurodegenerative diseases; Wheelchairs; Amyotrophic lateral sclerosis; Brain machine interface; Brain signals; Cognitive ability; Motor function; Open BCI; Quality of life; Third parties; Brain computer interface

In the present project it is focused on patients Amotrophy Lateral Sclerosis (ALS), so these patients do not have control of their motor functions therefore are unable to move on their own, requiring third party assistance to move with his wheelchair. Patients of Amyotrophic Lateral Sclerosis do not lose their cognitive ability, which is why you can use it to control his wheelchair as part of a computer chandler system using Cyton board of open BCI brain signals is extracted and with the help of deep learning classification of signals, so the patient can move their own means be held. In this project it was possible to perform communication computer brain, in addition to the proper functioning of the system, in addition it was possible to implement a security system that protects the patient against accidents, so the patient is safer to move; whole system gives the patient, partial independence and thus improve their quality of life.