Research Article
Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience
Table 2
The area under the receiver operating characteristic curve.
| Event | Receiver operating characteristic | EACL and SampEn via ANN | BIS and SampEn via ANN |
| Patient 1 | 0.996 | 1.000 | Patient 2 | 0.964 | 0.999 | Patient 3 | 0.998 | 0.982 | Patient 4 | 0.980 | 0.986 | Patient 5 | 0.973 | 0.897 | Patient 6 | 0.921 | 0.867 | Patient 7 | 1.000 | 0.997 | Patient 8 | 0.938 | 0.999 | Patient 9 | 0.798 | 0.604 | Patient 10 | 0.987 | 0.985 | Patient 11 | 0.917 | 0.964 | Patient 12 | 0.952 | 0.856 | Patient 13 | 0.999 | 0.997 | Patient 14 | 0.966 | 1.000 | Patient 15 | 0.944 | 0.920 | Patient 16 | 0.988 | 0.984 | Patient 17 | 0.999 | 0.993 | Patient 18 | 1.000 | 0.987 | Patient 19 | 0.964 | 0.974 | Patient 20 | 0.940 | 0.946 | Patient 21 | 0.985 | 0.965 | Patient 22 | 0.807 | 0.981 | Patient 23 | 0.994 | 0.896 | Patient 24 | 1.000 | 0.997 |
| Mean ± SD | 0.953 ± 0.07 | 0.949 ± 0.08 |
|
|