Research Article
Automatic Detection of Obstructive Sleep Apnea Events Using a Deep CNN-LSTM Model
Table 2
The parameters and TACs of the different models.
| | Name | N | Layer | Units | Size | Stride | TAC (%) |
| | Model_1 | 3 | Cn_1 | 24 | 125 × 1 | 1 × 1 | 94.832 | | Cn_2 | 24 | 15 × 1 | 1 × 1 | | Cn_3 | 24 | 5 × 1 | 1 × 1 | | Model_2 | 4 | Cn_1 | 24 | 125 × 1 | 1 × 1 | 94.835 | | Cn_2 | 20 | 100 × 1 | 1 × 1 | | Cn_3 | 24 | 15 × 1 | 1 × 1 | | Cn_4 | 24 | 5 × 1 | 1 × 1 | | Model_3 | 4 | Cn_1 | 24 | 125 × 1 | 1 × 1 | 93.92 | | Cn_2 | 20 | 50 × 1 | 1 × 1 | | Cn_3 | 20 | 15 × 1 | 1 × 1 | | Cn_4 | 20 | 5 × 1 | 1 × 1 | | Model_4 | 3 | Cn_1 | 24 | 100 × 1 | 1 × 1 | 94.78 | | Cn_2 | 24 | 15 × 1 | 1 × 1 | | Cn_3 | 24 | 5 × 1 | 1 × 1 | | Model_5 | 2 | Cn_1 | 30 | 125 × 1 | 1 × 1 | 90.4 | | Cn_2 | 30 | 15 × 1 | 1 × 1 |
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