A GCNN built from EEG spectral coherence and electrode distance classifies insomnia with 70% window accuracy, and channel-ablation tests highlight C4-P4, F4-C4 and C4-A1 as the most informative channels.
Electroencephalography and clinical neurophysiology103(5), 499–515 (1997)
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Graph Convolutional Neural Networks to Model the Brain for Insomnia
A GCNN built from EEG spectral coherence and electrode distance classifies insomnia with 70% window accuracy, and channel-ablation tests highlight C4-P4, F4-C4 and C4-A1 as the most informative channels.