Analysis of dyslexic children dynamic emotion trajectory during executive function tasks

Dyslexia is a language learning disability resulting in people experiencing difficulties in reading, spelling, writing and speaking due to inability in differentiating sound components. Detection of dyslexia for young children is a challenge because the signs and symptoms are not always obvious. It is also costly since experts are required to conduct and interpret the results of these evaluations. In this paper, the executive function tests were carried out on both control and dyslexic children and their respective brain waves are captured. By analyzing the electroencephalogram (EEG) patterns on the emotion dynamic while conducting the four executive functions, namely: identifying alphabet, recognizing colors, distinguishing between left and right and memory test, we are able to provide new insight into their emotional state. Kernel Density Estimation (KDE) feature extraction method coupled with Multi-layer Perceptron (MLP) are used to identify underlying different emotions during the executive function test. Experimental results indicated that there are substantial differences between dyslexic and control participants and the proposed method shows potential of extending such work for bigger scale analysis