Table 3.
Intra-subject fatigue classification using 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.
| Intra-subject classification | ||||
|---|---|---|---|---|
| Linear | Polynomial | RBF | ||
| General Features |
Accuracy | 0.97 | 0.88 | 0.96 |
| Sensitivity | 0.98 | 0.92 | 0.98 | |
| Specificity | 0.96 | 0.84 | 0.94 | |
| AUC | 0.98 | 0.98 | 0.98 | |
| Selected Features |
Accuracy | 0.93 | 0.86 | 0.93 |
| Sensitivity | 0.90 | 0.82 | 0.88 | |
| Specificity | 0.96 | 0.90 | 0.98 | |
| AUC | 0.96 | 0.94 | 0.97 | |