• DocumentCode
    1612804
  • Title

    EEG-Based Mental Task Classification in Hypnotized and Normal Subjects

  • Author

    Solhjoo, Soroosh ; Nasrabadi, Ali Motie ; Golpayegani, Mohammad Reza Hashemi

  • Author_Institution
    Biomed. Eng. Fac., Amirkabir Univ. of Technol., Tehran
  • fYear
    2006
  • Firstpage
    2041
  • Lastpage
    2043
  • Abstract
    EEG-based mental task classification is an approach to understand the processes in our brain which lead to our thoughts and behavior. Different mental tasks have been used for this purpose and we have chosen relaxation and imagination for our study. As well as normal conscious state, we have considered mental tasks performed in hypnosis which is defined as a state of consciousness with high concentration. To assess nonlinear dynamics, we have considered fractal dimension in addition to frequency features. HMM classifiers have been used for classification. Results show the most important features in EEG signal related to mentioned mental tasks as well as differences between normal and hypnotic states of the brain
  • Keywords
    electroencephalography; fractals; hidden Markov models; medical signal processing; signal classification; EEG-based mental task classification; HMM classifiers; brain; fractal dimension; hypnosis; hypnotized subjects; imagination; nonlinear dynamics; normal conscious state; normal subjects; relaxation; Biomedical engineering; Biomedical signal processing; Brain modeling; Electroencephalography; Feature extraction; Fractals; Frequency; Hidden Markov models; Problem-solving; Rhythm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1616858
  • Filename
    1616858