Table 7 Analysis summary
From: Review of EEG-based pattern classification frameworks for dyslexia
Research | Analysis method |
|---|---|
Different brain activation patterns in dyslexic children: evidence from EEG power and coherence patterns for the double-deficit theory of dyslexia [38] | Fast Fourier transform |
Wavelet entropy differentiations of event-related potentials in dyslexia [40] | Wavelet entropy |
Detecting complexity abnormalities in dyslexia measuring approximate entropy of electroencephalographic signals [39] | Approximate entropy and cross-approximate entropy |
Comparison between characteristics of EEG signal generated from dyslexic and normal children [42] | Fast Fourier transform |
An SVM-based algorithm for analysis and discrimination of dyslexic readers from regular readers using ERPs [45] | Time domain and frequency domain |
Classification of dyslexic and normal children during resting condition using KDE and MLP [46] | Short-time Fourier transform |
Wavelet packet analysis of EEG signals from children during writing [47] | Wavelet analysis |