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Predict Blood Pressure by Photoplethysmogram with the Fluid-Structure Interaction Modeling
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作者 Jianhong Chen Wenrui Hao +1 位作者 Pengtao Sun Lian Zhang 《Communications in Computational Physics》 SCIE 2022年第4期1114-1133,共20页
Blood pressure(BP)has been identified as one of the main factors in cardiovascular disease and other related diseases.Then how to accurately and conveniently measure BP is important to monitor BP and to prevent hypert... Blood pressure(BP)has been identified as one of the main factors in cardiovascular disease and other related diseases.Then how to accurately and conveniently measure BP is important to monitor BP and to prevent hypertension.This paper proposes an efficient BP measurement model by integrating a fluid-structure interaction model with the photoplethysmogram(PPG)signal and developing a data-driven computational approach to fit two optimization parameters in the proposedmodel for each individual.The developed BPmodel has been validated on a public BP dataset and has shown that the average prediction errors among the root mean square error(RMSE),the mean absolute error(MAE),the systolic blood pressure(SBP)error,and the diastolic blood pressure(DBP)error are all below 5mmHg for normal BP,stage I,and stage II hypertension groups,and,prediction accuracies of the SBP and the DBP are around 96%among those three groups. 展开更多
关键词 Blood pressure prediction fluid-structure interaction PPG
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