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EEG Signal Processing for BCI Applications

  • A. Roman-Gonzalez
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 98)

Abstract

In this article we offer a communication system to people who undergo a severe loss of motor function as a result of various accidents and/or diseases so that they can control and interact better with the environment, for which a brain-computer interface has been implemented through the acquisition of EEG signals by electrodes and implementation of algorithms to extract characteristics and execute a method of classification that would interpret these signals and execute corresponding actions The first objective is to design and construct a system of communication and control based on the thought, able to catch and measure EEG signals. The second objective is to implement the system of data acquisition including a digital filter in real time that allows us to eliminate the noise. The third objective is to analyze the variation of the EEG signals in front of the different tasks under study and of implementing an algorithm of extraction of characteristics. The fourth objective is to work on the basis of the characteristics of the EEG signals, to implement a classification system that can discriminate between the two tasks under study on the basis of the corresponding battles.

Keywords

Amyotrophic Lateral Sclerosis Little Mean Square Brain Computer Interface Beta Band Frequency Band Alpha 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • A. Roman-Gonzalez
    • 1
  1. 1.Department of Electronics EngineeringUniversidad Nacional San Antonio, Abad del CuscoPeru

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