# Blood Pressure Monitoring Based on Flexible Encapsulated Sensors
## 5 Conclusions  
This study investigated a sensor packaging method based on the combination of parylene and PDMS to address the issues of traditional pressure sensors in blood pressure monitoring. The encapsulated sensor exhibited high sensitivity and accuracy and could capture good pulse signals when installed in a wristband. Additionally, a blood pressure measurement method based on the combination of arterial tonometry and pulse wave analysis was developed. Specifically, a new feature set was formed by combining the extracted pulse wave features with the initial blood pressure values obtained from arterial tonometry, and multiple machine learning algorithms were used for regression analysis to achieve accurate blood pressure measurement. Among them, the random forest regression algorithm produced the smallest mean absolute error and standard deviation values for systolic and diastolic blood pressure and met the AAMI standard commonly used in clinical practice. The proposed method blood pressure monitoring based on flexible packaged sensors has great potential for precise the diagnosis and treatment of diseases such as hypertension.  
This study addressed the limitations of traditional pressure sensors in the field of blood pressure monitoring by designing and implementing a novel blood pressure monitoring system using flexible encapsulated sensors. The following achievements were obtained:  
(1) A sensor encapsulation method was developed by combining parylene and PDMS, resulting in highly sensitive and accurate encapsulated sensors. These sensors were integrated into wristbands, allowing for the reliable acquisition of pulse signals.  
(2) An improved arterial tonometry blood pressure measurement method was proposed. It involved combining extracted pulse wave feature parameters with preliminary blood pressure values obtained through arterial tonometry. Regression analysis using various machine learning algorithms was performed to achieve accurate blood pressure measurement.  
(3) The results from multiple experiments demonstrated that the proposed system improved the accuracy of systolic and diastolic blood pressure measurements by 31.4% and 21%, respectively, compared with those of the arterial tonometry method. Among  
Figure 11: Bland\(-\)Altman plot showing mean difference and 95% limits of agreement: (**a**) SBP; (**b**) DBP.  
the regression models used, the random forest algorithm exhibited the highest precision in predicting blood pressure, and the measured systolic and diastolic pressures met the widely accepted AAMI standards.  
In summary, the proposed blood pressure monitoring system based on flexible encapsulated sensors shows potential for wearable blood pressure measurement and holds significant application prospects in the precise diagnosis and treatment of conditions such as hypertension.  
Conceptualization, W.S. and W.C.; methodology, W.S. and W.C.; software, W.C.; validation, W.S. and W.C.; formal analysis, W.C.; investigation, W.C.; resources, W.S.; data curation, W.S.; writing original draft preparation, W.S. and W.C.; writing review and editing, W.S. and W.C.; visualization, W.S.; supervision, W.S.; project administration, W.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data that support the findings of this study are available from the author, upon reasonable request.  
The authors declare no conflict of interest.