Analysis of EEG signals of dyslexic children using wavelet packet decomposition: article / Norazah Fuad

This paper describes Wavelet Packet Decomposition of EEG signal of dyslexic children with writing disability. Two activities were carried out by the children during EEG recordings: relax and writing activities as well as letter recognization. EEG signal were collected using biosignal gMobilab system and MATLAB SIMULINK program. EEG collected data were then analysed using Wavelet Packet Decomposition to extract the brain wave rythm especially Alpha and Beta rythm. Statistical data such as log energy entropy and standard deviation also tabulated during the analysis process. Result shows that the dyslexic children consumed higher energy at left parietal lobe during writing activity especially who response incorrectly. Also, the alpha band shows higher log energy entropy for dyslexic children compare to normal children at most channel during relax condition.