Optoelectronics Letters, Volume. 16, Issue 6, 467(2020)
Real-time human blood pressure measurement based on laser self-mixing interferometry with extreme learning machine
In this paper, we present a method based on self-mixing interferometry combing extreme learning machine for real-time human blood pressure measurement. A signal processing method based on wavelet transform is applied to extract reversion point in the self-mixing interference signal, thus the pulse wave profile is successfully reconstructed. Considering the blood pressure values are intrinsically related to characteristic parameters of the pulse wave, 80 samples from the MIMIC-II database are used to train the extreme learning machine blood pressure model. In the experiment, 15 measured samples of pulse wave signal are used as the prediction sets. The results show that the errors of systolic and diastolic blood pressure are both within 5 mmHg compared with that by the Coriolis method.
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WANG Xiu-lin, Lü Li-ping, HU Lu, HUANG Wen-cai. Real-time human blood pressure measurement based on laser self-mixing interferometry with extreme learning machine[J]. Optoelectronics Letters, 2020, 16(6): 467
Received: Mar. 17, 2020
Accepted: May. 30, 2020
Published Online: Dec. 25, 2020
The Author Email: Wen-cai HUANG (huangwc@xmu.edu.cn)