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Low cost brain computer interface system for ar.drone control

by Rafael Mendes Duarte

Institution: Universidade Federal de Santa Catarina
Year: 2017
Posted: 02/01/2018
Record ID: 2171524
Full text PDF: https://repositorio.ufsc.br/xmlui/handle/123456789/180243


Abstract

Abstract : This work presents the design, implementation, and testing of a Brain-Computer Interface (BCI) system based on -waves to control the navigation of a drone. BCI systems perform the translation of brain signals into commands to communicate with external applications. The rhythm is a type of brain signal response to motor activity which can be easily measured by electroencephalography (EEG). For this reason, -waves based BCI systems have been extensively explored in the literature as a way of enabling patients with compromised neuromotor functions to interact with the outside world. To implement the signal processing and application interface routines, a software platform was built based on well-established filter and classification techniques, such as the Common Spatial Patterns (CSP) and the Linear Discriminant Analysis (LDA). For interfacing with the drone, an algorithm for translating the classifier outputs into drone commands was proposed. In addition, the acquisition of brain waves was performed by a low-cost and open-hardware EEG amplifier called OpenBCI. The validation of the designed system was performed using public and an acquired motor imagery EEG datasets, which were supplied to the platform to simulate the real-time performance of the system. The tests, conducted in a drone simulator, demonstrated the correct operation of the proposed methodology and the designed system. ; Este trabalho apresenta o projeto, implementao e teste de um sistema de Interface Crebro Mquina (BCI) baseado em ondas para o controle da navegao de um drone comercial. Sistemas BCI realizam a traduo dos sinais cerebrais em comandos que podem ser usados para ativao e controle de aplicaes externas. O ritmo um tipo de resposta cerebral que modulado atravs da atividade motora e pode ser facilmente medido atravs de eletroencefalografia (EEG). Por este motivo, sistemas BCI baseados em ondas tem sido extensivamente explorados na literatura como uma forma de permitir que pacientes com sistema neuromotor comprometido interajam com o ambiente externo. Neste trabalho, uma plataforma de software foi desenvolvida para implementar as rotinas de processamento de sinal e de interface com a aplicao. Tnicas bem estabelecidas como o filtro espacial CSP e o classificador LDA foram utilizadas para realizar a de-teco dos padres cerebrais. Alm disso, proposta uma metodologia para traduzir o sinal de sada do classificador em comandos que podem ser diretamente enviados para o drone. Para aquisio dos sinais de EEG, um amplificador de baixo custo e open-source chamado Open-BCI foi utilizado. A implementao do sistema foi validada atravs de um conjunto de dados pblico, que foram utilizados na plataforma como forma de simular o comportamento em tempo-real do sistema. Os testes de aplicao foram conduzidos em um simulador do drone, o que demonstrou o correto funcionamento da metodologia proposta e do sistema desenvolvido.Advisors/Committee Members: Trofino Neto, Alexandre (advisor).

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