Sensor fusion in human blood pressure measurements using oscillometric and auscultatory principles: Error analysis and implementation

Abstract

The accurate measurement of human blood pressure is a growing needs in the recent years, to obtain the prior information about the heart related risks. Majority of the available blood pressure measurement systems are based on the principle of auscultation and oscillometric method, operated independently. In this work, we develop a low-cost blood pressure measurement system based on auscultation and oscillometric principle. We present the complementary information fusion approach to combine auscultation and oscillometric signals to improve overall accuracy of the system. However, the parameters for our complementary information fusion is optimized based on the simulated sample data points generated using Windkessel model. We presents the extensive experimental validation results to measure systolic and diastolic pressure for three different categories of patients that includes Hypotension, Normal and Hypertension. The better average measurement accuracy of 90.84 percent is obtained using our approach of complementary information fusion for Alpha = 0.5 value on simulated sample data. Further, we use the optimized complementary fusion operator with Alpha = 0.5 in our developed system and the measurement obtained with our method is compared against the reference meter with minimum measurement errors, demonstrating the potential of our system in measuring accurately the blood pressure.