Real-time human blood pressure measurement based on laser self-mixing interferometry with extreme learning machine  

作　　者：WANG Xiu-lin LÜLi-ping HU Lu HUANG Wen-cai 王秀琳;吕莉萍;胡路;黄文财(Department of Physics,Jimei University,Xiamen 361021,China;Department of Electronics Engineering,Xiamen University,Xiamen 361005,China)

机构地区：[1]Department of Physics,Jimei University,Xiamen 361021,China [2]Department of Electronics Engineering,Xiamen University,Xiamen 361005,China

出　　处：《Optoelectronics Letters》2020年第6期467-470,共4页光电子快报（英文版）

基　　金：supported by the National Natural Science Foundation of China (No.61675174);the Natural Science Foundation of Fujian Province (No.2020J01705)。

摘　　要：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 mm Hg compared with that by the Coriolis method.

关 键 词：PROFILE Real-time human blood pressure measurement based on laser self-mixing interferometry with extreme learning machine 

分 类 号：TN911.7[电子电信—通信与信息系统] R443.5[电子电信—信息与通信工程]