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. 2024 Nov 2;11:1192. doi: 10.1038/s41597-024-03951-4

Table 5.

Performance of models using baseline view.

Model Time Frequency
KH MS RW-T RW-W UCI WDM Mean KH MS RW-T RW-W UCI WDM Mean
KNN 42.4% 81.0% 31.0% 46.1% 54.6% 60.4% 52.6% 86.8% 88.9% 73.6% 68.9% 81.7% 93.5% 82.2%
Random Forest 80.6% 87.9% 74.1% 77.4% 85.5% 92.1% 82.9% 79.7% 91.0% 83.8% 76.2% 92.2% 97.0% 86.7%
SVM 57.6% 76.9% 81.1% 68.8% 85.7% 92.5% 77.1% 70.1% 84.7% 85.5% 79.9% 86.2% 98.6% 84.2%
CNN (1D)12 77.5% 93.4% 80.8% 73.0% 95.2% 95.6% 85.9% 75.0% 91.2% 82.4% 82.9% 94.5% 96.6% 87.1%
CNN (2D)12 76.0% 93.2% 71.3% 77.7% 95.3% 91.5% 84.1% 79.6% 91.8% 79.6% 78.6% 89.1% 95.5% 85.7%
CNN PF34 79.4% 93.2% 70.7% 73.8% 94.2% 88.1% 83.3% 82.1% 92.1% 77.5% 83.2% 92.9% 96.6% 87.4%
CNN PFF34 79.4% 93.5% 73.4% 72.6% 95.8% 89.7% 84.1% 85.0% 90.4% 78.5% 83.3% 93.2% 96.3% 87.8%
ConvNet13 75.0% 93.5% 68.3% 74.2% 91.9% 90.5% 82.2% 87.6% 91.5% 86.3% 82.3% 95.0% 96.9% 89.9%
IMU CNN14 75.0% 87.4% 60.0% 64.3% 89.6% 84.8% 76.8% 84.2% 91.7% 75.6% 78.7% 94.1% 96.6% 86.8%
IMU Transf.14 74.9% 70.5% 73.0% 74.2% 92.2% 89.4% 79.0% 72.2% 73.1% 78.5% 76.9% 78.8% 96.3% 79.3%
MLP (2 Layers) 75.0% 83.2% 77.8% 63.3% 79.9% 91.4% 78.4% 86.7% 92.7% 82.5% 77.5% 92.8% 97.9% 88.4%
MLP (3 layers) 78.8% 82.7% 76.4% 64.5% 80.8% 88.6% 78.6% 86.2% 90.5% 81.7% 76.9% 93.7% 98.5% 87.9%
ResNet15 79.6% 86.8% 74.6% 76.9% 97.6% 91.9% 84.6% 70.4% 86.0% 80.5% 71.4% 92.8% 93.6% 82.5%
ResNetSE67 78.2% 90.9% 72.2% 76.1% 97.4% 92.9% 84.6% 76.2% 82.7% 80.3% 76.1% 91.6% 94.1% 83.5%
ResNetSE-567 78.6% 89.0% 70.0% 75.3% 95.3% 90.4% 83.1% 76.1% 90.3% 79.0% 78.2% 92.5% 94.5% 85.1%
Max 80.6% 93.5% 81.1% 77.7% 97.6% 95.6% 85.9% 87.6% 92.7% 86.3% 83.3% 95.0% 98.6% 89.9%

The best results for each dataset and for each domain (time and frequency) are highlighted in bold. Mean column represents the average performance of the model in the datasets.