Article
Version 1
Preserved in Portico This version is not peer-reviewed
Research on Blood Pressure Monitoring Based on Flexible Encapsulated Sensors
*
and
Version 1
: Received: 17 May 2023 / Approved: 18 May 2023 / Online: 18 May 2023 (10:42:15 CEST)
A peer-reviewed article of this Preprint also exists.
Sun, W.; Chang, W. Blood Pressure Monitoring Based on Flexible Encapsulated Sensors. Appl. Sci. 2023, 13, 7473. Sun, W.; Chang, W. Blood Pressure Monitoring Based on Flexible Encapsulated Sensors. Appl. Sci. 2023, 13, 7473.
Abstract
In order to realize the accurate measurement of wearable sphygmomanometer, this paper selects the micro electro mechanical system (MEMS) pressure sensor with small size, low cost and high accuracy, and proposes a flexible packaging method combining Parylene and Polydimethylsiloxane (PDMS). The flexible packaging sensor protects the sensor chip while ensuring the comfort of the measured person. It can be worn for a long time, and the encapsulated sensor has good accuracy and sensitivity. At the same time, the encapsulated MEMS pressure sensor was used to collect good pulse signals and extract multiple pulse wave characteristic parameters. A blood pressure measurement method based on the combination of arterial tonometry method and pulse wave parameters method was proposed, and multiple machine learning algorithms were compared and analyzed to select the algorithm model with the smallest error as the optimal regressor. The experimental results show that the blood pressure measurement method combining the arterial tonometry method and the pulse wave parameters method can effectively improve the accuracy of blood pressure measurement. The experimental results demonstrate that the combination of arterial tonometry and pulse wave parameter methods can effectively enhance the accuracy of blood pressure measurement, with the random forest model serving as the optimal regressor. The average deviation between the systolic blood pressure measured by our self-made sphygmomanometer and the commercial sphygmomanometer was 0.86mmHg, with a standard deviation of 4.04mmHg. The average deviation of diastolic blood pressure was 0.63mmHg, with a standard deviation of 5.15mmHg, meeting the AAMI standard for clinical practice.
Keywords
Continuous blood pressure measurement; MEMS pressure sensor; Flexible packaging; Machine learning
Subject
Engineering, Electrical and Electronic Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
