Design And Implementation Of Pulse Wave Sensing System Based On Laser Self-mixing Interference

Optical interference technology is an important method in the field of precision machining and inspection.In recent years,self-mixing interferometry(SMI)with self-mixing effect as the theoretical c.ore has rapidly risen in optical measurement due to its characteristics including single optical path,easy alignment and high sensitivity.attracting more and more scholars' attention.The theoretical study of SMI becoming complete,its related application research expands to vibration,velocity,distance,laser parameter,biomedicine and other fields.The SMI effect can be defined as the phenomenon that the emitted laser is reflected or scattered by the external object,and carries the information of the external object back to the laser cavity,then couples with the laser in the laser cavity,thus modulating the laser output power and frequency.The information of external objects can be obtained by analyzing and processing the fluctuating optical power,namely the SMI signal.The main purpose of this paper is to apply the SMI technology to pulse wave signal acquisition and analysis,and introduce the support vector machine(SVM)algorithm,to achieve the acquisition and classification of pulse waves.This paper first reviews the development of SMI theory and summarizes its application research actuality.Then the internal mechanism of SMI effect is comprehensively explained from the rotation vector model,F-P three-cavity mirror theory and L-K rate equation theory,and the power and phase equation of SMI is deduced to construct the mathematical model of SMI system.The influence of various parameters of the system on the SMI signal is analyzed by MATLAB simulation.Then the hardware system of micro-vibration measurement and real-time display based on SMI is designed and built.The system includes signal sensing optical path,pretreatment circuit,rectifier circuit and DSP signal processing module.The correctness of numerical simulation and the validity of vibration measurement of hardware system are verified by experiments.Finally,the pulse wave classification model is established with SVM algorithm.And the SVM classification model has been trained based on the PhsioBank database.The accuracy of the prediction results reaches 91.8%,indicating the feasibility of the pulse wave classification model in this paper.In this paper,the pulse wave measurement and classification system compared to the traditional pressure sensing system with finger or wrist clamped has the advantage of non-contact,which provides a new ef-fective way for pulse condition diagnosis and human health evaluation,and partly promotes the progress that SMI technique is applied to medical signal noninvasive detection.