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Fractal-Based Brain State Recognition from EEG in Human Computer Interaction

  • Olga Sourina
  • Qiang Wang
  • Yisi Liu
  • Minh Khoa Nguyen
Part of the Communications in Computer and Information Science book series (CCIS, volume 273)

Abstract

Real-time brain states recognition from Electroencephalogram (EEG) could add a new dimension in an immersive human-computer interaction. As EEG signal is considered to have a fractal nature, we proposed and developed a general fractal based spatio-temporal approach to brain states recognition including the concentration level, stress level, and emotion recognition. Our hypothesis is that changes of fractal dimension values of EEG over time correspond to the brain states changes. Overall brain state recognition algorithms were proposed and described. Fractal dimension values were calculated by the implemented Higuchi and Box-counting methods. Real-time subject-dependent classification algorithms based on threshold FD values calculated during a short training session were proposed and implemented. Based on the proposed real-time algorithms, neurofeedback games for concentration and stress management training such as “Brain Chi”, “Dancing Robot”, “Escape”, and “Apples”, and emotion-enabled applications such as emotion-enabled avatar, music therapy, and emotion-based search were designed and implemented.

Keywords

BCI Neurofeedback Emotion recognition Fractal dimension EEG Real-time applications 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Olga Sourina
    • 1
  • Qiang Wang
    • 1
  • Yisi Liu
    • 1
  • Minh Khoa Nguyen
    • 1
  1. 1.Nanyang Technological UniversitySingapore

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