Table 8.
Comparison of performance of the proposed approach against other state-of-the-art algorithms for the AFIB detection task on the MIT-BIH AFIB database with the ECG segment of size 5-s.
| Work | Approach | Best Performance (%) |
|||
|---|---|---|---|---|---|
| accuracy | ppv | sensitivity | specificity | ||
| ELP | CNN | 98.17 | 97.78 | 98.57 | 97.76 |
| ELP | RNN | 97.93 | 97.63 | 98.24 | 97.61 |
| ELP | RNN-Attention | 97.96 | 97.87 | 98.08 | 97.84 |
| Xia et al. [34] | SWT + CNN | 98.63 | - | 98.79 | 97.87 |
| Asgari et al. [4] | SWT + SVM | - | - | 97.00 | 97.10 |
| Jiang et al. [9] | RR interval irregularity + P-wave absence | - | - | 98.20 | 97.50 |
ppv: positive predictive value; SWT: stationary wavelet transform