Table 3 Evaluation of different models for estimating BP from PAT or PTT.
A posteriori models | Population-based models | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Model | RMSE | MAE | MAD | Model | RMSE | MAE | MAD | |||
PAT | BP = \(\frac{{\text{a}}}{{\text{PAT}}}\) + b | SBP | 5.50 | 3.63 | 4.14 | Poon16 | SBP | 11.04 | 7.10 | 8.46 |
DBP | 4.49 | 3.42 | 2.92 | DBP | 8.37 | 6.12 | 5.71 | |||
BP = \(\frac{{\mathbf{a}}}{{\mathbf{PAT}}^2}\) + b | SBP | 5.48 | 3.61 | 4.12 | Gesche18 | SBP | 43.76 | 21.63 | 38.06 | |
DBP | 4.49 | 3.42 | 2.92 | DBP | 46.70 | 22.93 | 40.71 | |||
BP = a\(\times \)ln(PAT) + b | SBP | 5.53 | 3.66 | 4.15 | Fung37 | SBP | 8.51 | 5.70 | 6.33 | |
DBP | 4.50 | 3.42 | 2.92 | DBP | 8.02 | 5.90 | 5.43 | |||
PTT | BP = \(\frac{{\text{a}}}{{\text{PTT}}}\) + b | SBP | 3.98 | 2.82 | 2.81 | Poon16 | SBP | 8.49 | 5.40 | 6.56 |
DBP | 4.02 | 3.12 | 2.54 | DBP | 7.72 | 5.64 | 5.26 | |||
BP = \(\frac{{\mathbf{a}}}{{\mathbf{PTT}}^2}\) + b | SBP | 3.91 | 2.78 | 2.76 | Gesche18 | SBP | 4542 | 1773 | 4185 | |
DBP | 4.01 | 3.12 | 2.53 | DBP | 4546 | 1776 | 4188 | |||
BP = a\(\times \)ln(PTT) + b | SBP | 4.05 | 2.86 | 2.87 | Fung37 | SBP | 30.69 | 20.77 | 22.61 | |
DBP | 4.03 | 3.12 | 2.55 | DBP | 33.80 | 22.45 | 25.29 |