Table 2 Comparison of the proposed framework with other previous systems.
From: Securing Internet-of-Medical-Things networks using cancellable ECG recognition
Work | Dataset | EER | Accuracy (%) |
|---|---|---|---|
Barros et al.19 | PhysioNet | N/A | 92 |
Su et al.21 | ECG-ID | 0.144 | 75.71 |
Zhang et al.22 | ptbdb, mitdb, nsrdb | 1.57 | 97.6 |
Hammad et al.23 | MIT-BIH | 6 | N/A |
Kim et al.24 | ECG-ID | 2.6 | 94.3 |
Zhao et al.25 | ECG-ID | 5.68 | 96.6 |
Blasco et al.26 | Low-cost sensors biometrics | 2 | 99 |
Proposed framework at SNR = 10 dB | ECG-ID | 0.134 | 99.96 |
MIT-BIH | 0.4 | 99.96 |
