Table 1.
EEG automatic classification (* = severe AD ** = mild AD; S. no. = Sample; N. aged = normal aged; ANN = artificial neural networks; LDA = linear discriminant analysis; ACC = accuracy (%); SE = sensibility; SP = specificity).
| Author year | S. no. | AD | N. aged | MCI | Length (s) | Classificators | ACC | SE | SP | |
|---|---|---|---|---|---|---|---|---|---|---|
| ANN | LDA | |||||||||
| Pritchard et al. (1994) | 39 | 14 | 25 | nd | x | x | 85 | nd | nd | |
| Besthorn et al. (1997) | nd | nd | nd | nd | x | x | 86.60 | |||
| Huang et al. [6, 11] | 93 | 38 | 24 | 31 | nd | x | 81 | 84 | 78 | |
| Knott et al. (2001) | 65 | 35 | 30 | nd | x | 75 | ||||
| Petrosian et al. [17] | 20 | 10 | 10 | 120 | x | 90 | 80 | 100 | ||
| Cichocki et al. [20] | 60 | 38 | 22 | 20 | x | 78.25 | 73 | 84 | ||
| Melissant et al. [16] | 36 | 15* | 21 | 40 | x | 94 | 93 | 95 | ||
| Melissant et al. [16] | 38 | 28** | 10 | 40 | x | 82 | 64 | 100 | ||