Journal
SENSORS
Volume 19, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/s19040848
Keywords
microstructure; polymer sensor; pulse-wave monitoring; machine learning technique; blood-pressure estimation
Funding
- National Science Council, Taiwan [106-2221-E-002-213-MY3]
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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 (-0.533 kPa(-1)) 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-2 = 0.871 for SBP and R-2 = 0.794 for DBP, respectively.
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