Article ID Journal Published Year Pages File Type
562848 Biomedical Signal Processing and Control 2006 11 Pages PDF
Abstract

Phase synchrony and model-based magnitude squared (MS) coherence analyses of the EEG are investigated for their usefulness in the discrimination between non-ADHD and ADHD children.We observed that phase synchrony is higher – on average – for non-ADHD participants than for the ADHD group. Based on the relatively small sample available to us, we find that a Euclidean distance-based classifier may – with selection of proper electrode pairs, EEG rhythm, and task – discriminate between the EEG of non-ADHD and ADHD children with an average percentage of correct classification of 63.2%.MS coherence was observed to be considerably higher at low frequencies (i.e. below 1 Hz) for ADHD subjects than for the majority of the non-ADHD individuals. We also observed that the θ rhythm MS coherence (approximately 4–6 Hz) is generally higher for non-ADHD subjects than for ADHD individuals. The combination of these effects was observed on four out of the seven non-ADHD subjects and on all six of the ADHD subjects.

Related Topics
Physical Sciences and Engineering Computer Science Signal Processing
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