Journal
JOURNAL OF MICROMECHANICS AND MICROENGINEERING
Volume 27, Issue 2, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1361-6439/27/2/024002
Keywords
cuff-less blood pressure estimation; pulse arrival time; signal quality index; Kalman filter
Categories
Funding
- National Natural Science Foundation of China [61302033]
- National Key Research and Development Project [2016YFC1304302]
- Key Project of Beijing Municipal Natural Science Foundation [Z16003]
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The present study designs an algorithm to increase the accuracy of continuous blood pressure (BP) estimation. Pulse arrival time (PAT) has been widely used for continuous BP estimation. However, because of motion artifact and physiological activities, PAT-based methods are often troubled with low BP estimation accuracy. This paper used a signal quality modified Kalman filter to track blood pressure changes. A Kalman filter guarantees that BP estimation value is optimal in the sense of minimizing the mean square error. We propose a joint signal quality indice to adjust the measurement noise covariance, pushing the Kalman filter to weigh more heavily on measurements from cleaner data. Twenty 2 h physiological data segments selected from the MIMIC II database were used to evaluate the performance. Compared with straightforward use of the PAT-based linear regression model, the proposed model achieved higher measurement accuracy. Due to low computation complexity, the proposed algorithm can be easily transplanted into wearable sensor devices.
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