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Previous issue date: 2017-03-30 / Brain-Machine Interface (BCI) or Brain-Computer Interface (BCI) is a computer system capable of establishing communication between human neurophysiological activity and a computer. A hybrid BCI (hBCI) consists of a combination of two or more types of BCIs, two or more signal acquisition techniques, or a combination of BCI with other non-BCI based interaction techniques. A Collaborative BCI (cBCI) integrates the brain activity of a group of individuals, mainly acting in the increase of the human capacity. Low-cost electroencephalogram (EEG) equipment is currently available in the market, one of which is the Emotiv EEG, which is portable, has 14 electrodes, and in addition to registering the neurophysiological signals, it processes and makes available them in the form of neural measurements, such as levels of attention and excitement. In addition to neural measures, other measures may reveal an individual's behavior, such as the speed with which he responds to a challenge, which may suggest how confident he is about this decision-making. This work has as main objective "To verify if neural and behavioral measures have relation with the right and wrong decision making". Initially, a systematic review of the literature was carried out. Afterwards, a data collection system and a decision-making task based on Rapid Serial Visual Presentation (RSVP) were developed. The experiment consisted of 10 participants, in which each one performed 112 tests, recording the neural measurements taken by Emotiv EEG, besides the Reaction Time (RT) as a behavioral measure and the response given by the user, both collected by a conventional keyboard. Statistical techniques, such as descriptive analysis, including data summarization and boxplot charts, and multivariate analysis were used for the data analysis, using logistic regression to estimate the relationship between neural and behavioral measures with the decisions made. The proposed task proved to be efficient, revealing in the results that the difficulty was effective. The developed database proved to be efficient in synchronizing the task data and the recorded measurements. After different approaches of statistical analysis of the data, a regression model that could explain with high explanatory power the data sampled was not found. Thus, based on the experiment performed and statistical analyzes, no relationship was found between neural and behavioral measures and the correct or wrong decision-making. / Interface C?rebro-M?quina (ICM) ou Interface C?rebro-Computador (ICC) ? um sistema computacional capaz de estabelecer a comunica??o entre a atividade neurofisiol?gica humana e um computador. Uma ICC h?brida (ICCh) consiste na combina??o de dois ou mais tipos de ICC, duas ou mais t?cnicas de aquisi??o de sinal, ou, ainda, da combina??o de uma ICC com outras t?cnicas de intera??o n?o baseadas em ICC. Uma ICC Colaborativa (ICCc) integra a atividade cerebral de um grupo de indiv?duos, atuando, principalmente, no aumento da capacidade humana. Atualmente, no mercado, est?o dispon?veis equipamentos de Eletroencefalograma (EEG) de baixo custo, sendo um desses o Emotiv EEG, que ? port?til, possui 14 eletrodos, e, al?m e registrar os sinais neurofisiol?gicos, os processa e disponibiliza em forma de medidas neurais, como, por exemplo, n?veis de aten??o e excitamento. Al?m de medidas neurais, outras medidas podem revelar o comportamento de um indiv?duo, como, por exemplo, a velocidade com que responde um desafio, que pode sugerir o qu?o confiante ele est? sobre esta tomada de decis?o. Este trabalho tem como principal objetivo ?Verificar se medidas neurais e comportamentais possuem rela??o com as tomadas de decis?o corretas e erradas?. Inicialmente, foi realizada uma revis?o sistem?tica da literatura. Ap?s, foram desenvolvidos um sistema de coleta de dados e uma tarefa de tomada de decis?o baseada em Rapid Serial Visual Presentation (RSVP). O experimento contou com 10 participantes, no qual cada um executou 112 ensaios, sendo registradas as medidas neurais captadas pelo Emotiv EEG, al?m do Tempo de Rea??o (RT) como medida comportamental e, a resposta dada pelo usu?rio, ambas coletadas por um teclado convencional. Para a an?lise dos dados, foram aplicadas t?cnicas de estat?stica, tais como an?lise descritiva, incluindo sumariza??o dos dados e gr?ficos de boxplots, e an?lise multivariada, utilizando regress?o log?stica para estimar a rela??o entre medidas neurais e comportamentais com as decis?es tomadas. A tarefa proposta mostrou-se eficiente, revelando nos resultados que a dificuldade empregada se mostrou efetiva. O banco de dados desenvolvido mostrou-se eficiente na sincroniza??o dos dados da tarefa e as medidas registradas. Ap?s diferentes abordagens de an?lise estat?stica dos dados, n?o foi encontrado um modelo de regress?o que pudesse explicar com alto poder explicativo os dados amostrados. Desta maneira, baseado no experimento realizado e nas an?lises estat?sticas, n?o foram encontradas rela??es entre medidas neurais e comportamentais e as tomadas de decis?o corretas ou erradas.
| Identifer | oai:union.ndltd.org:IBICT/oai:tede2.pucrs.br:tede/7711 |
| Date | 30 March 2017 |
| Creators | Schuh, ?nderson Rodrigo |
| Contributors | Campos, M?rcia de Borba |
| Publisher | Pontif?cia Universidade Cat?lica do Rio Grande do Sul, Programa de P?s-Gradua??o em Ci?ncia da Computa??o, PUCRS, Brasil, Faculdade de Inform?tica |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da PUC_RS, instname:Pontifícia Universidade Católica do Rio Grande do Sul, instacron:PUC_RS |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 1974996533081274470, 500, 500, 500, -3008542510401149144, -862078257083325301 |
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