Research Article
Deep Convolutional Neural Network Based ECG Classification System Using Information Fusion and One-Hot Encoding Techniques
Table 6
VEB and SVEB classification performance (%) of the proposed method and a comparison with the results of previous studies on 24 testing records (DS2).
| Methods | VEB | SVEB | Acc | Sen | Spe | Ppr | Acc | Sen | Spe | Ppr |
| Jiang and Kong [35] | 98.1 | 86.6 | 99.3 | 93.3 | 96.6 | 50.6 | 98.8 | 67.9 | Ince et al. [36] | 97.6 | 83.4 | 98.1 | 89.5 | 96.1 | 62.1 | 98.5 | 56.7 | Kiranyaz et al. [5] | 98.6 | 95.0 | 98.1 | 89.5 | 96.4 | 64.6 | 98.6 | 62.1 | Zhai and Tin. [18] | 98.6 | 93.8 | 99.2 | 92.4 | 97.5 | 76.8 | 98.7 | 74.0 | Proposed | 98.2 | 99.3 | 87.3 | 98.7 | 99.5 | 99.4 | 99.9 | 99.9 |
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