• DocumentCode
    3761806
  • Title

    EEG average FFT index for dyslexic children with writing disorder

  • Author

    S.N. Farihah;Khuan Y. Lee;W. Mansor;N. B. Mohamad;Z. Mahmoodin;S. A Saidi

  • Author_Institution
    Faculty of Electrical Engineering, Computational Physiologic Detection RIG, Pharmaceutical &LifeSciences Community of Research, Universiti Teknologi MARA, 40450 Shah Alam, Selangor DE, Malaysia
  • fYear
    2015
  • Firstpage
    118
  • Lastpage
    121
  • Abstract
    Dyslexia is a neurological disorder that needs to be detected at an early stage for recovery through efficient intervention. It is defined as difficulty with learning due to impairment to the left hemisphere of the brain associated with language processing. It is often misinterpreted as being lazy, which has a negative impact on the self-confidence of the children. Electroencephalography (EEG) is the recording of electrical fields produced by neuronal activity obtained from the scalp surface after being picked up by metal electrodes and conductive gel. Most of the previous works on dyslexia are based on subjective and psychometric methods, focused on reading and spelling mainly. Our research here is a preliminary study to investigate if EEG average FFT index is able to provide signature characteristics for dyslexic children with writing disorder, where no previous attempt has been reported. In this study, EEG signals from eight electrodes along the neuropathway for writing were sampled. Daubechies 8 (DB8) wavelet function and Fast Fourier Transform (FFT) were used to extract the frequency content features from EEG signals. EEG of poor and capable dyslexic is recorded to examine the brain activation regions in writing sentences and nonsense sentences. Differences in hemispheric activation are found in writing sentences and nonsense sentences, between poor and capable dyslexic.
  • Keywords
    "Electroencephalography","Writing","Indexes","Electrodes","Scalp","Fast Fourier transforms","Biomedical engineering"
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering & Sciences (ISSBES), 2015 IEEE Student Symposium in
  • Type

    conf

  • DOI
    10.1109/ISSBES.2015.7435880
  • Filename
    7435880