A Highly Sensitive Pressure-Sensing Array for Blood Pressure Estimation Assisted by Machine-Learning Techniques

This work describes the development of a pressure-sensing array for noninvasive continuous blood pulse-wave monitoring. The sensing elements comprise a conductive polymer film and interdigital electrodes patterned on a flexible Parylene C substrate. The polymer film was patterned with microdome stru...

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Bibliographic Details
Main Authors: Kuan-Hua Huang, Fu Tan, Tzung-Dau Wang, Yao-Joe Yang
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/4/848
Description
Summary:This work describes the development of a pressure-sensing array for noninvasive continuous blood pulse-wave monitoring. The sensing elements comprise a conductive polymer film and interdigital electrodes patterned on a flexible Parylene C substrate. The polymer film was patterned with microdome structures to enhance the acuteness of pressure sensing. The proposed device uses three pressure-sensing elements in a linear array, which greatly facilitates the blood pulse-wave measurement. The device exhibits high sensitivity (&#8722;0.533 kPa<sup>&#8722;1</sup>) and a fast dynamic response. Furthermore, various machine-learning algorithms, including random forest regression (RFR), gradient-boosting regression (GBR), and adaptive boosting regression (ABR), were employed for estimating systolic blood pressure (SBP) and diastolic blood pressure (DBP) from the measured pulse-wave signals. Among these algorithms, the RFR-based method gave the best performance, with the coefficients of determination for the reference and estimated blood pressures being R<sup>2</sup> = 0.871 for SBP and R<sup>2</sup> = 0.794 for DBP, respectively.
ISSN:1424-8220