Research Article
Wrist EMG Monitoring Using Neural Networks Techniques
Table 7
Classification performance indicators.
| | MAV | RMS | WL | VAR |
| Precision | Extension | 0.8868 | 0.9600 | 0.8381 | 0.6000 | Flexion | 0.9126 | 0.9333 | 0.8241 | 0.6667 | Pronation | 0.8544 | 0.9592 | 0.7387 | 0.6100 | Supination | 0.9000 | 0.9794 | 0.8586 | 0.5313 | Accuracy | Extension | 0.9400 | 0.9886 | 0.833 | 0.8244 | Flexion | 0.9400 | 0.9795 | 0.9592 | 0.8244 | Pronation | 88.0000 | 0.9726 | 0.8269 | 0.8244 | Supination | 90.0000 | 0.9532 | 0.9631 | 0.8244 | Recall | Extension | 0.9400 | 1.0000 | 0.8889 | 0.6000 | Flexion | 0.9400 | 1.0000 | 0.89 | 0.5891 | Pronation | 0.8800 | 0.9307 | 0.8817 | 0.5169 | Supination | 0.9000 | 0.8962 | 0.8763 | 0.6869 | F1-score | Extension | 0.9129 | 0.9796 | 0.8628 | 0.6000 | Flexion | 0.9261 | 0.9657 | 0.8559 | 0.6251 | Pronation | 0.8669 | 0.9447 | 0.8042 | 0.5600 | Supination | 0.9000 | 0.9356 | 0.8673 | 0.6000 |
|
|