Study of Electroencephalography signal of autism and Down syndrome children using FFT

摘要

Electroencephalography (EEG) signal between normal and special children is slightly different. Different types of special children will generate different shape of EEG patterns depend on their neurological function. This paper demonstrates the classification of EEG signal for special children: to determine and to classify level and pattern of EEG signal for autism and Down syndrome children. EEG signal was recorded and captured from normal and special children based on their visual response using Visual Evoked Potential (VEP) method. The data is analyzed using Fast Fourier Transform (FFT), so that, normal and special children can be distinguished based on alpha (α) value. As a result, alpha value for normal children at 10 Hz is higher than autism and Down syndrome children. A friendly user interface was built for easy storage and visualization.