A non-invasive continuous cuffless blood pressure estimation using dynamic Recurrent Neural Networks

2020 ◽  
Vol 170 ◽  
pp. 107534
Author(s):  
Umit Senturk ◽  
Kemal Polat ◽  
Ibrahim Yucedag
Author(s):  
Ming Hua Yeh ◽  
Paul C.-P. Chao ◽  
Rajeev Pandey

Abstract Blood pressure is a basic physiological quantity and prolonged abnormal blood pressure which will precipitate different kinds of cardiovascular diseases. The early detection of hypertension is extremely important for the prevention and cure of cardiovascular diseases. This study proposes a new on-chip real-time algorithm for non-invasive cuffless blood pressure estimation using PPG Sensor (PPG). The algorithm is implemented in the integrated chip with chip area of 3.97mm2 and fabricated via TSMC T18 process. The experimental result shows that the overall power consumption of the chip is 15.62 mW. Finally, the blood pressure measurement platform has been developed with GUI for long-term continuous cuffless BP measurement. The non-invasive blood pressure sensor is applied to the wrist artery of 44 subjects for sensing the PPG pulsation of the blood vessel. Measurement results shows that the maximum error in the BP measurement is ±6 mmHg. Which is less than 8 mmHg, defined by the Advancement of Medical Instrumentation (AAMI) and British Hypertension Society (BHS) standard.


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