Attention-deficit hyperactivity disorder (ADHD) is a neurobiological condition mostly affecting children. The diagnosis and treatment of ADHD has been a controversial subject among researchers. In this study, we analyzed the accountability of using theta/beta ratio and beta activations as EEG-based biomarkers for assessing the brain activity acquired during an attention task in ADHD children (n = 7) and normal control subjects (n = 7). ADHD subjects showed reduced beta activity during the task and higher theta/beta ratio at rest, in line with previous research findings. Furthermore, most of the ADHD subjects, during the attention test, presented a beta power falling outside the normality range defined on the normal children group.

EEG analysis of brain activity in attention deficit hyperactivity disorder during an attention task

Coelli, S.;Bianchi, A. M.;
2017-01-01

Abstract

Attention-deficit hyperactivity disorder (ADHD) is a neurobiological condition mostly affecting children. The diagnosis and treatment of ADHD has been a controversial subject among researchers. In this study, we analyzed the accountability of using theta/beta ratio and beta activations as EEG-based biomarkers for assessing the brain activity acquired during an attention task in ADHD children (n = 7) and normal control subjects (n = 7). ADHD subjects showed reduced beta activity during the task and higher theta/beta ratio at rest, in line with previous research findings. Furthermore, most of the ADHD subjects, during the attention test, presented a beta power falling outside the normality range defined on the normal children group.
2017
RTSI 2017 - IEEE 3rd International Forum on Research and Technologies for Society and Industry, Conference Proceedings
9781538639061
ADHD; EEG; Sustained Attention; Theta/beta; Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Energy Engineering and Power Technology; Industrial and Manufacturing Engineering; Health (social science); Management of Technology and Innovation; Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1040058
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