Table 9 Blood pressure
Publication year | Author | Publication title | Population/dataset | Purpose of study | Sensors | Framework | Diseases | Performance |
|---|---|---|---|---|---|---|---|---|
2020 [203] | Soh et al. | Computers in Biology and Medicine | MIT-BIH NSRDB, SHAREE DB | A CNN-based model for diagnosing hypertension via ECG | ECG | CNN | HPT | Acc = 99.99% |
2020 [207] | Li et al. | Sensors | MIMIC II DB | An LSTM-based model evaluates blood pressure in real time via ECG and PPG | ECG、PPG | LSTM | Blood pressure | MAE(SBP/DBP) = 6.726/2.516 STD(SBP/DBP) = 14.505/6.442 |
2020 [205] | Miao et al. | Artificial Intelligence in Medicine | MIMIC III DB, Proprietary DB | A ResLSTM model assesses blood pressure in real time via ECG | ECG | CNN、LSTM | Blood pressure | MD(SBP/DBP) = − 0.12/0.01/ − 0.03 STD(SBP/DBP) = 9.99/6.29/6.36 |
2021 [208] | Jeong et al. | Scientific Reports | MIMIC | A CNN-LSTM model evaluates blood pressure in real time via ECG and PPG | ECG、PPG | CNN-LSTM | Blood pressure | MAD(SBP/DBP) = 1.2/1.0 SD(SBP/DBP) = 1.6/1.3 |
2021 [209] | Esmaelpoor et al. | Physiological Measurement | MIMIC-II DB | The CNN-based model assesses blood pressure in real time via ECG and PPG | ECG、PPG | CNN | Blood pressure | MAE(SBP/DBP) = 3.28/1.75 SD(SBP/DBP) = 5.38/2.75 |
2021 [215] | Yang et al. | Optical and Quantum Electronics | Proprietary DB | A hybrid DL model based on CNN assesses blood pressure in real time via ECG and PPG | ECG、PPG | CNN、LSTM、Dense | Blood pressure | MAE(SBP/DBP) = 4.43/3.23 SD(SBP/DBP) = 6.09/4.75 |
2022 [212] | Zabihi et al. | Biomedical Signal Processing and Control | MIMIC DB | A TCN-based model evaluates blood pressure in real time via ECG and PPG | ECG、PPG | TCN | Blood pressure | MAE(SBP/DBP) = 2.59/1.33 STD(SBP/DBP) = 3.5837/1.9742 |
2022 [213] | Huang et al. | Biomedical Signal Processing and Control | MIMIC DB, UQVS DB | An MLP-BP model evaluates blood pressure in real time via ECG and PPG | ECG、PPG | MFMC、MLP、LSTM、gMLP | Blood pressure | MAE(SBP/DBP) = 3.52/2.13 SD(SBP/DBP) = 5.09/3.07 |
2022 [214] | Yen et al. | IEEE Access | MIMIC-II DB | A CNN-based model for real-time blood pressure assessment by ECG and PPG is proposed | ECG、PPG | CNN、LSTM、GRU | Blood pressure | ME(SBP/DBP) = 0.02/-0.1 SD(SBP/DBP) = 3.59/2.56 |
2022 [216] | Jo et al. | Plos ONE | Vital DB | The Resnet-based model predicts IOH in real time through ECG and ABP | ECG、ABP、EEG | Resnet | IOH | 3 /5/10/15 min AUROC = 0.970/0.935/0.898/0.894 AUPRC = 0.943/0.882/0.819/0.808 |
2022 [210] | Baker et al. | Knowledge-Based Systems | MIMIC-III DB | A CNN-LSTM model evaluates blood pressure in real time via ECG and PPG | ECG、PPG | CNN-LSTM | Blood pressure | MAE(SBP/DBP) = 4.53/3.37 SD(SBP/DBP) = 6.27/4.84 |
2023 [206] | Long et al. | Biomedical Signal Processing and Control | MIMIC DB | A BPNet model evaluates blood pressure in real time via ECG and PPG | ECG、PPG | CNN,FPN | Blood pressure | ME(SBP/DBP) = -0.17/-0.24 STD(SBP/DBP) = 4.62/2.95 |
2023 [211] | Wang et al. | Frontiers in Digital Health | MIMIC III DB, VitalDB | A CNN-based model for real-time blood pressure assessment by ECG and PPG is proposed and a usable PulseDB dataset is presented | ECG、PPG | CNN | Blood pressure | SDE(SBP/DBP) = 2.76/3.09 MAE(SBP/DBP) = 2.00/2.11 |