From: Review of EEG-based pattern classification frameworks for dyslexia
Research | Test group size | Control group size | Total |
---|---|---|---|
Different brain activation patterns in dyslexic children: Evidence from EEG power and coherence patterns for the double-deficit theory of dyslexia [38] | 19 | 19 | 38 |
Wavelet entropy differentiations of event-related potentials in dyslexia [40] | 38 | 19 | 57 |
Detecting complexity abnormalities in dyslexia measuring approximate entropy of electroencephalographic signals [39] | 38 | 19 | 57 |
Comparison between characteristics of EEG signal generated from dyslexic and normal children [42] | 3 | 3 | 6 |
An SVM-based algorithm for analysis and discrimination of dyslexic readers from regular readers using ERPs [45] | 20 | 30 | 50 |
Classification of dyslexic and normal children during resting condition using KDE and MLP [46] | 3 | 3 | 6 |
Wavelet packet analysis of EEG signals from children during writing [47] | 4 | 4 | 8 |
Mean sample size (rounded) | 18 | 15 | 32 |