BPNet: A multi-modal fusion neural network for blood pressure estimation using ECG and PPG

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Published in	Biomedical signal processing and control Vol. 86; p. 105287
Main Authors	Long, Weicai, Wang, Xingjun
Format	Journal Article
Language	English
Published	01.09.2023
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ArticleNumber	105287
Author	Wang, Xingjun Long, Weicai
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References	10.1016/j.bspc.2023.105287_b0160 Yao (10.1016/j.bspc.2023.105287_b0125) 2021; 44 Kachuee (10.1016/j.bspc.2023.105287_b0175) 2017; 64 Athaya (10.1016/j.bspc.2023.105287_b0030) 2021; 21 Hsu (10.1016/j.bspc.2023.105287_b0115) 2020; 20 Yan (10.1016/j.bspc.2023.105287_b0200) 2019 Baek (10.1016/j.bspc.2023.105287_b0235) 2019; 7 Goldberger (10.1016/j.bspc.2023.105287_b0170) 2000; 101 Slapničar (10.1016/j.bspc.2023.105287_b0025) 2019; 19 Mehrabadi (10.1016/j.bspc.2023.105287_b0035) 2022 O??Brien (10.1016/j.bspc.2023.105287_b0220) 1990; 8 Branco (10.1016/j.bspc.2023.105287_b0060) 2018 Hill (10.1016/j.bspc.2023.105287_b0140) 2021; 11 Bote (10.1016/j.bspc.2023.105287_b0110) 2020; 84 Branco (10.1016/j.bspc.2023.105287_b0050) 2017 10.1016/j.bspc.2023.105287_b0135 10.1016/j.bspc.2023.105287_b0155 10.1016/j.bspc.2023.105287_b0055 Shin (10.1016/j.bspc.2023.105287_b0080) 2023; 60 10.1016/j.bspc.2023.105287_b0195 Hu (10.1016/j.bspc.2023.105287_b0180) 2022; 10 10.1016/j.bspc.2023.105287_b0090 10.1016/j.bspc.2023.105287_b0190 He (10.1016/j.bspc.2023.105287_b0210) 2021 Jeong (10.1016/j.bspc.2023.105287_b0215) 2021; 11 Steininger (10.1016/j.bspc.2023.105287_b0070) 2021; 110 Miao (10.1016/j.bspc.2023.105287_b0130) 2020; 108 Stergiou (10.1016/j.bspc.2023.105287_b0225) 2018; 71 Quan (10.1016/j.bspc.2023.105287_b0095) 2021; 21 Si (10.1016/j.bspc.2023.105287_b0045) 2022; 217 Sharifi (10.1016/j.bspc.2023.105287_b0230) 2019; 97 Malayeri (10.1016/j.bspc.2023.105287_b0145) 2022; 12 TaheriNejad (10.1016/j.bspc.2023.105287_b0120) 2020 Qin (10.1016/j.bspc.2023.105287_b0040) 2021; 70 Zong (10.1016/j.bspc.2023.105287_b0185) 2003 10.1016/j.bspc.2023.105287_b0005 Vardhan (10.1016/j.bspc.2023.105287_b0015) 2021 Mousavi (10.1016/j.bspc.2023.105287_b0205) 2019; 47 Ren (10.1016/j.bspc.2023.105287_b0075) 2022 10.1016/j.bspc.2023.105287_b0100 Ding (10.1016/j.bspc.2023.105287_b0105) 2019; 9 Cepeda (10.1016/j.bspc.2023.105287_b0010) 2023; 46 10.1016/j.bspc.2023.105287_b0065 10.1016/j.bspc.2023.105287_b0165 10.1016/j.bspc.2023.105287_b0085 Tatliparmak (10.1016/j.bspc.2023.105287_b0150) 2023; 67 Yoon (10.1016/j.bspc.2023.105287_b0240) 2018; 22 10.1016/j.bspc.2023.105287_b0020
References_xml	– volume: 44 start-page: 397 issue: 2 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0125 article-title: Cuff-less blood pressure estimation from photoplethysmography signal and electrocardiogram publication-title: Phys. Eng. Sci. Med. doi: 10.1007/s13246-021-00989-1 – ident: 10.1016/j.bspc.2023.105287_b0190 doi: 10.1109/CVPR.2017.106 – start-page: 1917 year: 2019 ident: 10.1016/j.bspc.2023.105287_b0200 article-title: Novel deep convolutional neural network for cuff-less blood pressure measurement using ECG and PPG signals – volume: 97 start-page: 143 year: 2019 ident: 10.1016/j.bspc.2023.105287_b0230 article-title: A novel dynamical approach in continuous cuffless blood pressure estimation based on ECG and PPG signals publication-title: Artif. Intell. Med. doi: 10.1016/j.artmed.2018.12.005 – volume: 19 start-page: 3420 issue: 15 year: 2019 ident: 10.1016/j.bspc.2023.105287_b0025 article-title: Blood pressure estimation from photoplethysmogram using a spectro-temporal deep neural network publication-title: Sensors doi: 10.3390/s19153420 – volume: 101 issue: 23 year: 2000 ident: 10.1016/j.bspc.2023.105287_b0170 article-title: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals publication-title: Circulation doi: 10.1161/01.CIR.101.23.e215 – volume: 7 start-page: 185458 year: 2019 ident: 10.1016/j.bspc.2023.105287_b0235 article-title: End-to-end blood pressure prediction via fully convolutional networks publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2960844 – ident: 10.1016/j.bspc.2023.105287_b0020 – volume: 108 start-page: 101919 year: 2020 ident: 10.1016/j.bspc.2023.105287_b0130 article-title: Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques publication-title: Artif. Intell. Med. doi: 10.1016/j.artmed.2020.101919 – start-page: 67 year: 2018 ident: 10.1016/j.bspc.2023.105287_b0060 article-title: Rebagg: Resampled bagging for imbalanced regression – ident: 10.1016/j.bspc.2023.105287_b0100 doi: 10.1109/ICBBT.2010.5479013 – ident: 10.1016/j.bspc.2023.105287_b0085 doi: 10.3390/ma16062133 – start-page: 1495 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0015 article-title: BP-Net: Efficient Deep Learning for Continuous Arterial Blood Pressure Estimation using Photoplethysmogram – start-page: 36 year: 2017 ident: 10.1016/j.bspc.2023.105287_b0050 article-title: SMOGN: a pre-processing approach for imbalanced regression[C]//First international workshop on learning with imbalanced domains: Theory and applications publication-title: PMLR – ident: 10.1016/j.bspc.2023.105287_b0160 doi: 10.1109/ICNN.1994.374138 – ident: 10.1016/j.bspc.2023.105287_b0135 doi: 10.1109/SMARTCOMP.2016.7501681 – volume: 12 start-page: 6633 issue: 1 year: 2022 ident: 10.1016/j.bspc.2023.105287_b0145 article-title: Concatenated convolutional neural network model for cuffless blood pressure estimation using fuzzy recurrence properties of photoplethysmogram signals publication-title: Sci. Rep. doi: 10.1038/s41598-022-10244-6 – volume: 21 start-page: 1867 issue: 5 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0030 article-title: An estimation method of continuous non-invasive arterial blood pressure waveform using photoplethysmography: A U-Net architecture-based approach publication-title: Sensors doi: 10.3390/s21051867 – volume: 70 start-page: 102972 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0040 article-title: Deep generative model with domain adversarial training for predicting arterial blood pressure waveform from photoplethysmogram signal publication-title: Biomed. Signal Process. Control doi: 10.1016/j.bspc.2021.102972 – volume: 11 start-page: 13539 issue: 1 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0215 article-title: Combined deep CNN–LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features publication-title: Sci. Rep. doi: 10.1038/s41598-021-92997-0 – ident: 10.1016/j.bspc.2023.105287_b0005 – volume: 9 start-page: 37 issue: 1 year: 2019 ident: 10.1016/j.bspc.2023.105287_b0105 article-title: Pulse transit time technique for cuffless unobtrusive blood pressure measurement: from theory to algorithm publication-title: Biomed. Eng. Lett. doi: 10.1007/s13534-019-00096-x – start-page: 7926 year: 2022 ident: 10.1016/j.bspc.2023.105287_b0075 article-title: Balanced mse for imbalanced visual regression – volume: 11 issue: 1 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0140 article-title: Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning publication-title: Sci. Rep. doi: 10.1038/s41598-021-94913-y – ident: 10.1016/j.bspc.2023.105287_b0155 doi: 10.1201/9780203753736 – volume: 10 start-page: 649 issue: 8 year: 2022 ident: 10.1016/j.bspc.2023.105287_b0180 article-title: Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition and Genetic Algorithm-Optimized Wavelet Threshold Denoising publication-title: Machines doi: 10.3390/machines10080649 – start-page: 3 year: 2020 ident: 10.1016/j.bspc.2023.105287_b0120 article-title: Blood pressure estimation using a single ppg signal – volume: 217 start-page: 108120 year: 2022 ident: 10.1016/j.bspc.2023.105287_b0045 article-title: Nonlinear degradation modeling and prognostics: A Box-Cox transformation perspective publication-title: Reliab. Eng. Syst. Saf. doi: 10.1016/j.ress.2021.108120 – volume: 47 start-page: 196 year: 2019 ident: 10.1016/j.bspc.2023.105287_b0205 article-title: Blood pressure estimation from appropriate and inappropriate PPG signals using A whole-based method publication-title: Biomed. Signal Process. Control doi: 10.1016/j.bspc.2018.08.022 – start-page: 1906 year: 2022 ident: 10.1016/j.bspc.2023.105287_b0035 article-title: Novel blood pressure waveform reconstruction from photoplethysmography using cycle generative adversarial networks – volume: 60 start-page: e14173 issue: 2 year: 2023 ident: 10.1016/j.bspc.2023.105287_b0080 article-title: A novel method for non-invasive blood pressure estimation based on continuous pulse transit time: An observational study publication-title: Psychophysiology doi: 10.1111/psyp.14173 – volume: 110 start-page: 2187 issue: 8 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0070 article-title: Density-based weighting for imbalanced regression publication-title: Mach. Learn. doi: 10.1007/s10994-021-06023-5 – volume: 84 start-page: 106616 year: 2020 ident: 10.1016/j.bspc.2023.105287_b0110 article-title: Evaluation of blood pressure estimation models based on pulse arrival time publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2020.106616 – ident: 10.1016/j.bspc.2023.105287_b0055 doi: 10.1007/978-3-642-40669-0_33 – volume: 46 start-page: 620 issue: 3 year: 2023 ident: 10.1016/j.bspc.2023.105287_b0010 article-title: Status of ambulatory blood pressure monitoring and home blood pressure monitoring for the diagnosis and management of hypertension in the US: an up-to-date review publication-title: Hypertens. Res. doi: 10.1038/s41440-022-01137-2 – volume: 20 start-page: 5668 issue: 19 year: 2020 ident: 10.1016/j.bspc.2023.105287_b0115 article-title: Generalized deep neural network model for cuffless blood pressure estimation with photoplethysmogram signal only publication-title: Sensors doi: 10.3390/s20195668 – volume: 64 start-page: 859 issue: 4 year: 2017 ident: 10.1016/j.bspc.2023.105287_b0175 article-title: Cuffless blood pressure estimation algorithms for continuous health-care monitoring publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2016.2580904 – start-page: 898 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0210 article-title: Novel Cuffless Blood Pressure Estimation Method Using a Bayesian Hierarchical Model – volume: 71 start-page: 368 issue: 3 year: 2018 ident: 10.1016/j.bspc.2023.105287_b0225 article-title: A universal standard for the validation of blood pressure measuring devices: Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO) Collaboration Statement publication-title: Hypertension doi: 10.1161/HYPERTENSIONAHA.117.10237 – ident: 10.1016/j.bspc.2023.105287_b0195 – volume: 8 start-page: 607 issue: 7 year: 1990 ident: 10.1016/j.bspc.2023.105287_b0220 article-title: The British Hypertension Society protocol for the evaluation of automated and semi-automated blood pressure measuring devices with special reference to ambulatory systems publication-title: J. Hypertens. doi: 10.1097/00004872-199007000-00004 – volume: 67 start-page: 120 year: 2023 ident: 10.1016/j.bspc.2023.105287_b0150 article-title: Agreement of Oscillometric and Auscultatory blood pressure measurement methods: An ambulance noise simulation study publication-title: Am. J. Emerg. Med. doi: 10.1016/j.ajem.2023.02.022 – ident: 10.1016/j.bspc.2023.105287_b0065 – ident: 10.1016/j.bspc.2023.105287_b0165 – start-page: 259 year: 2003 ident: 10.1016/j.bspc.2023.105287_b0185 article-title: An open-source algorithm to detect onset of arterial blood pressure pulses – volume: 22 start-page: 1068 issue: 4 year: 2018 ident: 10.1016/j.bspc.2023.105287_b0240 article-title: Cuff-less blood pressure estimation using pulse waveform analysis and pulse arrival time publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2017.2714674 – volume: 21 start-page: 4273 issue: 13 year: 2021 ident: 10.1016/j.bspc.2023.105287_b0095 article-title: Advances in non-invasive blood pressure monitoring publication-title: Sensors doi: 10.3390/s21134273 – ident: 10.1016/j.bspc.2023.105287_b0090
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