• DocumentCode
    3120319
  • Title

    A study on hybrid model of HMMs and GMMs for mirror neuron system modeling using EEG signals

  • Author

    Park, Seung-Min ; Park, Junheong ; Ko, Kwang-Eun ; Sim, Kwee-Bo

  • Author_Institution
    Sch. of Electr. Electron. Eng., Chung-Ang Univ., Seoul, South Korea
  • fYear
    2011
  • fDate
    27-30 June 2011
  • Firstpage
    2752
  • Lastpage
    2755
  • Abstract
    For our present life anytime, anywhere access to the network can communicate with the ubiquitous computing, it is essential to human life. We should be able to agree that communication will be enabled. For our present life, anytime, anywhere access to the network can communicate with the ubiquitous computing. Such as the ubiquitous era approached, interaction between the user and the computer has become an important issue. In this paper we use EEG signals to extract the user´s intention recognition data, which the Mirror Neuron System Based on HMMs and GMMs to model the convergence of the hybrid model is proposed. This is based on a kind of biological signals using EEG signals to the user´s intention recognition techniques have been studied. In addition, EEG signals is generated based on the model, using the user intention recognition method have been studied. The proposed model will be applied in the field of neuro robotics.
  • Keywords
    Gaussian processes; electroencephalography; hidden Markov models; human-robot interaction; medical signal processing; ubiquitous computing; EEG signal; Gaussian mixture model; biological signal; hidden Markov model; human robot interaction; mirror neuron system modeling; network access; neuro robotics; ubiquitous computing; user intention recognition data; Biological system modeling; Brain modeling; Electroencephalography; Hidden Markov models; Humans; Mirrors; Neurons; EEG; GMMs(Gaussian Mixture Models); HMMs(Hidden Markov Models); Intention recognition; Mirror Neuron System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-7315-1
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2011.6007503
  • Filename
    6007503