• DocumentCode
    134540
  • Title

    Alpha and beta EEG brainwave signal classification technique: A conceptual study

  • Author

    Zainuddin, Balkis Solehah ; Hussain, Z. ; Isa, Iza Sazanita

  • Author_Institution
    Fac. of Electr. Eng., Univ. Teknol. MARA, Minden, Malaysia
  • fYear
    2014
  • fDate
    7-9 March 2014
  • Firstpage
    233
  • Lastpage
    237
  • Abstract
    This paper presents a conceptual of EEG analysis and classification of brainwaves signal for alpha and beta signals during Functional Electrical Stimulation, FES-assisted exercise. The characteristics of brainwave signals, data acquisition for electroencephalograph (EEG) signal and data session are identified. This paper also includes the criteria of the subject for both stroke patient and healthy person. The process of filtering the artifact and sampling the data were studied based on the established previous worked. In addition, a review on feature extraction for further classifying of brainwave signals stroke patients before and after performing FES-assisted exercised were also identified.
  • Keywords
    data acquisition; electroencephalography; feature extraction; signal classification; EEG brainwave signal classification technique; alpha signals; beta signals; data acquisition; data sampling; data session; electroencephalograph signal; feature extraction; functional electrical stimulation; Classification algorithms; Conferences; Electrodes; Electroencephalography; Feature extraction; IEEE Engineering in Medicine and Biology Society; Indexes; Electroencephalograph (EEG); Intelligent Classification; alpha; beta; signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing & its Applications (CSPA), 2014 IEEE 10th International Colloquium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4799-3090-6
  • Type

    conf

  • DOI
    10.1109/CSPA.2014.6805755
  • Filename
    6805755