In addition, this disease has some effects such as poor inhibitory control on adults with ADHD and affects the performance of their working memory. Recent studies performed on different populations have indicated that ADHD is observed in about 5% of children, with more frequency in boys. The symptoms of ADHD are by excessive activity, problems in paying attention, restlessness, and sudden behaviours. The obtained accuracy provides a significant improvement in comparison to the other similar studies in identifying and classifying children with ADHD.Īttention deficit hyperactivity disorder (ADHD) is known as a mental and behavioural disorder, develops from childhood into adulthood. Experiments on a set of EEG signal obtained from 50 ADHD and 26 normal cases yielded a sensitivity, specificity, and accuracy of 98, 92.31, and 96.05%, respectively.
Neuroguide symptom network radar map series#
For computing, the chaotic time series of obtained EEG in the brain frontal lobe (FP1, FP2, F3, F4, and Fz) need to be analysed. Lyapunov exponent, fractal dimension, correlation dimension and sample, fuzzy and approximate entropies are the non-linear extracted features. In this study, a new approach is proposed based on the combination of some non-linear features to distinguish ADHD from normal children. Hence, chaotic indices can be employed to classify the EEG signals.
It has been proved that the brain neuronal activity and its related EEG signals have chaotic behaviour. On the other hand, non-linear analysis methods are widely applied in processing the electroencephalogram (EEG) signals. Early diagnosis of ADHD is crucial for treating the disease and reducing its harmful effects on education, employment, relationships, and life quality.
0 kommentar(er)
