Table 3 The FDR value for the feature extraction methods
From: An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects
Subject | TemplateM | Haar (7) | db6(4) | 106CWT | DedicatedW |
|---|---|---|---|---|---|
106 | 12.781 | 1.098 | 5.004 | 6.409 | 9.072 |
116 | 16.204 | 3.856 | 13.851 | 14.391 | 30.078 |
119 | 30.882 | 2.279 | 6.970 | 11.562 | 37.488 |
200 | 10.937 | 1.156 | 6.542 | 5.853 | 8.136 |
201 | 44.911 | 0.449 | 13.613 | 13.637 | 37.534 |
203 | 6.146 | 0.005 | 0.889 | 0.434 | 4.080 |
207 | 1.818 | 0.457 | 1.831 | 0.659 | 1.688 |
208 | 19.283 | 2.293 | 15.109 | 11.629 | 32.354 |
210 | 5.777 | 0.780 | 3.064 | 2.289 | 6.236 |
213 | 9.592 | 0.772 | 5.481 | 2.986 | 20.721 |
214 | 1.891 | 0.312 | 1.378 | 1.562 | 5.516 |
215 | 13.458 | 0.088 | 1.162 | 1.488 | 6.338 |
221 | 21.050 | 0.576 | 8.558 | 12.860 | 33.630 |
223 | 1.085 | 1.155 | 2.156 | 4.963 | 4.818 |
228 | 7.765 | 1.372 | 5.088 | 8.809 | 18.488 |
233 | 4.094 | 1.645 | 3.567 | 4.624 | 31.035 |
Average | 12.980 | 1.143 | 5.891 | 6.510 | 17.951 |
Std. | 11.733 | 0.997 | 4.689 | 4.951 | 13.604 |