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Wavelet packet analysis of EEG signals from dyslexic children with writing disability

N Fuad, W Mansor, Khuan Y Lee

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 11, 2013
    PubMed

    Abstract:

    This paper describes Wavelet Packet Analysis of EEG signal of dyslexic children with writing disability. Two activities were carried out during EEG recordings; relax and and writing letters. EEG signals were collected using biosignal gMobilab system and analysed using Wavelet Packet Decomposition to extract alpha and beta brainwave rhythm. Statistical data such as log energy entropy and standard deviation were used to compare the characteristic of EEG signals from dyslexic and normal children. Result showed that the dyslexic children consumed higher energy at left parietal lobe during writing activity especially those who write incorrectly. The alpha band shows higher log energy entropy for dyslexic children compare to normal children at most channel during relax.

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