Table 6 Summary of best performance rates for each database
From: Time–frequency based feature selection for discrimination of non-stationary biosignals
Methodology | t–f | n rel | % Reduc. 1 | n=(n c ×n r ) | % Reduc. 2 | Accuracy | |
|---|---|---|---|---|---|---|---|
representation | |||||||
size | |||||||
PCG - | Method 4 | 245760, | 36864 | 85% | 21 | 94.30% | 98.20±1.99% |
Scenario 1 | Method 8 | (512×480) | 24576 | 90% | 70=(10×7) | 71.52% | 99.64±0.66% |
EEG - | Method 4 | 256000, | 25600 | 90% | 13 | 99.99% | 98.20±1.99% |
Scenario 2 | Method 8 | (512×500) | 102400 | 60% | 784=(28×28) | 70% | 98.72±1.23% |
EEG - | Method 4 | 256000, | 25600 | 90% | 13 | 99.99% | 91.00±1.94% |
Scenario 3 | Method 8 | (512×500) | 102400 | 60% | 784=(28×28) | 70% | 94.40±3.75% |