Table 4.
Inter-subject fatigue classification using forceplate and IMU derived features. Accuracy, sensitivity, specificity and AUC (area under the Receiver operating curve) are tabulated for three kinds of feature selections methods and three kernels.
| Inter-subject classification | ||||
|---|---|---|---|---|
| Linear | Polynomial | RBF | ||
| General Features |
Accuracy | 0.88 | 0.90 | 0.90 |
| Sensitivity | 0.88 | 0.92 | 0.92 | |
| Specificity | 0.88 | 0.88 | 0.88 | |
| AUC | 0.93 | 0.92 | 0.95 | |
| Selected Features |
Accuracy | 0.85 | 0.85 | 0.88 |
| Sensitivity | 0.80 | 0.82 | 0.86 | |
| Specificity | 0.90 | 0.88 | 0.90 | |
| AUC | 0.93 | 0.92 | 0.94 | |