Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Behnaz Sheikholeslami; Ghasem Sadeghi Bajestani; Reza Yaghoobi Karimui; Reyhaneh Zarifiyan
Volume 15, Issue 1 , May 2021, , Pages 29-46
Abstract
Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that can affect people of all ages in the community, especially children, and cause changes in their behavior. Previous studies have often focused on frequency domain processing or the nonlinear dynamic aspects of EEG signals ...
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Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that can affect people of all ages in the community, especially children, and cause changes in their behavior. Previous studies have often focused on frequency domain processing or the nonlinear dynamic aspects of EEG signals such as correlation dimension, fractal dimension, Lyapunov exponent, entropy, and recurrence rate of brain processes to differentiate individuals with ADHD. In this study, we evaluate the volume of the EEG signal oscillation basin using Poincare sections in the phase space of EEG signals of people with ADHD and healthy people and sort this space as well as extract various geometric features. We present a different perspective of complexity of brain activity and the level of dynamism of people with ADHD compared to healthy individuals. Finally, by evaluating the extracted features and using the SFS algorithm based on the RBF-SVM classifier, we were able to separate people with ADHD from healthy people in the groups of children and adults, with accuracy of 93.20±2.04 and 95.60±1.13. The results of this study showed that the volume of the EEG signal oscillation basin in people with ADHD was significantly higher than healthy people, which indicates an increase in the degree of dynamism and thus a decrease in the complexity of brain activity in these people. It was also identified in this study that the increase in the volume of the EEG signal oscillation basin in children is more than adults, which indicates an increase in the level of dynamism of children compared to adults. Therefore, ADHD and age can be introduced as two important factors in changing the volume of the EEG signal oscillation basin.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Nasrin Sho'ouri
Volume 14, Issue 2 , July 2020, , Pages 159-168
Abstract
Previous research has shown that eye movements in people with Attention Deficit Hyperactivity Disorder (ADHD) and healthy people were different, and it is possible that there is a difference between the two groups' EOG signals. Therefore, in the present study, the recorded EOG signals of 30 children ...
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Previous research has shown that eye movements in people with Attention Deficit Hyperactivity Disorder (ADHD) and healthy people were different, and it is possible that there is a difference between the two groups' EOG signals. Therefore, in the present study, the recorded EOG signals of 30 children with ADHD and 30 healthy children were examined during performing an attentional related task. For this purpose, the scaling exponents of the two groups' EOG signals were calculated and the differences between the two groups were examined using statistical tests. The EOG signals were then classified using a Growing Neural Gas network. The results show that the scaling exponents of the EOG signals in children with ADHD were significantly higher than that of healthy children (p < 0.001). This result shows that the decay slope of power spectrum in ADHD children is more as compared to healthy children. In addition, the EOG signals were classified into two groups with a detection accuracy of 72.22±2.8%. The results of this study could be used to design a course of treatment with EOG biofeedback to treat or reduce the symptoms of people with ADHD.