Table 2.
EEG-, ECG-, and eye-movement-based authentication.
| Studies | Techniques | Classification Algorithms | # Users | Performance |
|---|---|---|---|---|
| [33] | EEG | FFT | 23 | 11% EER |
| [34] | EEG | FFT | 23 | 79% accuracy |
| [35] | EEG | kNN | 50 | 97% CRR |
| [38] | ECG | 1DMRLBP | - | 10.10% EER, 1.57% FAR, 0.39% FRR |
| [39] | ECG | ZMCP | 19 | 100% accuracy, 0.36% EER |
| [40] | ECG | kNN-DDM | - | 84.8% accuracy, 0.2% EER |
| [41] | Eye movement | SVM | 20 | 88.73% accuracy, 10.61% EER |
| [42] | Eye movement | SRC | 30 | 93.1% accuracy, 6.9% EER |
| [43] | Eye movement | SVM | 22 | 3.93% EER |
| [44] | Eye movement | SVM | - | 97.95% accuracy |
| [45] | Eye blink | CNN | CEW | 98.4% accuracy |
| [46] | BioAura | SVM, AB | - | 1.9% EER, 7.6% FAR, 9.6–8.4% FRR |