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

• 来源期刊: 光电子快报（英文版）
• 年，卷（期）: 2020,（6）
• 所属期刊栏目: Measurement Devices and Methods
• 页码范围: 467-470
• 页数: 4页
• 语种: 英文
• DOI: 10.1007/s11801-020-0050-x

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 mmHg compared with that by the Coriolis method.