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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Interface c?rebro-computador h?brida e colaborativa no processo de tomada de decis?o

Schuh, ?nderson Rodrigo 30 March 2017 (has links)
Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-11-01T19:16:41Z No. of bitstreams: 1 DIS_ANDERSON_RODRIGO_SCHUH_COMPLETO.pdf: 4835434 bytes, checksum: 8955e506f3216fd9bb93fba6d988ec02 (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-11-01T19:16:50Z (GMT) No. of bitstreams: 1 DIS_ANDERSON_RODRIGO_SCHUH_COMPLETO.pdf: 4835434 bytes, checksum: 8955e506f3216fd9bb93fba6d988ec02 (MD5) / Made available in DSpace on 2017-11-01T19:17:02Z (GMT). No. of bitstreams: 1 DIS_ANDERSON_RODRIGO_SCHUH_COMPLETO.pdf: 4835434 bytes, checksum: 8955e506f3216fd9bb93fba6d988ec02 (MD5) 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.
2

Um sistema inteligente de classifica??o de sinais de EEG para Interface C?rebro-Computador

Barbosa, Andr? Freitas 24 February 2012 (has links)
Made available in DSpace on 2014-12-17T14:56:05Z (GMT). No. of bitstreams: 1 AndreFB_DISSERT.pdf: 2147554 bytes, checksum: 3ed5f0d06e3b072597f2eae69b7d1ca2 (MD5) Previous issue date: 2012-02-24 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The Brain-Computer Interfaces (BCI) have as main purpose to establish a communication path with the central nervous system (CNS) independently from the standard pathway (nervous, muscles), aiming to control a device. The main objective of the current research is to develop an off-line BCI that separates the different EEG patterns resulting from strictly mental tasks performed by an experimental subject, comparing the effectiveness of different signal-preprocessing approaches. We also tested different classification approaches: all versus all, one versus one and a hierarchic classification approach. No preprocessing techniques were found able to improve the system performance. Furthermore, the hierarchic approach proved to be capable to produce results above the expected by literature / As interfaces c?rebro-computador (ICC) t?m como objetivo estabelecer uma via de comunica??o com o sistema nervoso central (SNC) que seja independente das vias padr?o (nervos, m?sculos), visando o controle de algum dispositivo. O objetivo principal da presente pesquisa ? desenvolver uma ICC off-line que separe os diferentes padr?es de EEG resultantes de tarefas puramente mentais realizadas por um sujeito experimental, comparando a efic?cia de diferentes abordagens de pr?-processamento do sinal. Tamb?m foram testadas diferentes abordagens de classifica??o: todos contra todos, um contra um e uma abordagem hier?rquica de classifica??o. N?o foram encontradas t?cnicas de pr?-processamento que melhorem os resultados do sistema. Al?m disso, a abordagem hier?rquica sugerida mostrou-se capaz de produzir resultados acima do padr?o esperado pela literatura

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