Table 1 Optimal classification results and performance comparisons in the three MI paradigms
From: A novel channel selection method for optimal classification in different motor imagery BCI paradigms
Subjects | Dataset 1 | Dataset 2 | Dataset 3 | ||||||
|---|---|---|---|---|---|---|---|---|---|
MI tasks Parad | Two-class control Parad | Four-class control Parad | |||||||
All Ch | C3, C4, Cz | Opt Ch | All Ch | C3, C4, Cz | Opt Ch | All Ch | C3, C4, Cz | Opt Ch | |
Acc (%) | Acc (%) | Acc(%) | Acc (%) | Acc (%) | Acc (%) | Acc (%) | Acc (%) | Acc (%) | |
Sub1 | 67.8 | 88.9 | 92.8 | 95.6 | 92.7 | 99.3 | 75.5 | 69.4 | 87.1 |
Sub2 | 62.2 | 65.6 | 86.7 | 82.7 | 65.1 | 91.2 | 74.1 | 76.4 | 90.6 |
Sub3 | 62.2 | 61.7 | 82.8 | 85.9 | 51.8 | 94.1 | 76.3 | 72.7 | 83.3 |
Sub4 | 70.0 | 74.4 | 90.0 | 67.9 | 52.2 | 85.3 | 58.2 | 67.0 | 80.2 |
Sub5 | 71.1 | 79.4 | 90.0 | 93.5 | 76.2 | 96.1 | 63.4 | 63.4 | 77.6 |
Sub6 | 62.8 | 54.4 | 80.0 | 96.2 | 95.2 | 98.6 | 55.8 | 73.4 | 80.3 |
Sub7 | 64.4 | 69.4 | 80.0 | 92.2 | 93.8 | 98.1 | 77.7 | 71.2 | 81.8 |
Sub8 | 57.2 | 60.6 | 78.9 | 82.4 | 82.3 | 90.4 | 74.8 | 66.9 | 84.9 |
Mean | 64.7 | 69.3 | 85.2 | 87.1 | 76.2 | 94.1 | 69.5 | 70.1 | 83.2 |
Std | 4.6 | 11.2 | 5.4 | 9.5 | 18.0 | 4.9 | 8.8 | 4.2 | 4.2 |
p value | – | – | p = 7.0e−5 | – | – | p = 0.024 | – | – | p = 2.4e−4 |