Research And Realization Of Multi-physiological Parameters Measurement Based On Single-lead Pulse Wave

With the entry of our country into the aging society stage,the health problem of the elderly population is one of the urgent problems to be solved in the public health field.The biggest threat to middle and old people's health is cardiovascular disease.Therefore,the reflection of cardiovascular health status of various types of physiological parameters detection is particularly important.However,the current vascular elasticity,blood pressure and microcirculation testing equipment are too expensive and bulky,can not be applied to the daily household physiological parameters of detection.This paper studies multiple physiological parameters detection algorithms and design the implementation of hardware and software side of multi-physiological parameter detection system are based on the study of Photoplethysmography(PPG).The main method of noninvasive arteriosclerosis detection is to extract PWV through dual-signal,its operation is complex,can not easily find some minor changes in arterial elasticity.And the value of the pulse volume characteristic K' of the index volume based on the single-conductivity pulse signal is too single and is not very sensitive to the change of the cardiovascular function of the elderly.In this paper,we present the characteristic parameters from the time domain,the frequency domain and the time-frequency domain to reflect the arterial elasticity,and compare the extracted characteristic parameters with the volumetric pulse characteristic K' which reflects the elasticity of the blood vessel.The experimental results show that the proposed characteristic parameters compared to K' can better reflect the vascular elasticity.Finally,the feature parameters are sent into the RBF neural network,and the measurement of the vascular elasticity is completed from the comprehensive angle.The output of the neural network is used to reflect the degree of arteriosclerosis.This paper presents a new blood pressure measurement model for the low correlation between diastolic blood pressure and pulse conduction time(PWTT)in the classical blood pressure measurement model of noninvasive blood pressure measurement.In addition to the PWTT parameters,this model also takes into account the vascular resistance and nerve regulation of a total of three factors on blood pressure.Compared with the original model,the accuracy of systolic blood pressure was measured according to the compensated multivariate model,and the results of measuring diastolic blood pressure were greatly improved.In the aspect of microcirculation measurement,this paper proposes a parameter estimation method of microcirculation volume pulse flow model based on nonlinear fitting.The microcirculation volume pulse flow model parameter R(microvascular peripheral resistance),L(Blood flow inertia),C(microvascular compliance)to explain the human microcirculation status.It is found that the microcirculation model parameters R,L and C are well reflected in the case where the K 'value is not sensitive to the microcirculation state,and the estimated parameters are compared with the index volume pulse wave characteristic K' which reflects the microcirculation.The state of microcirculation.Finally,the design and implementation of a single probe based on multi-physiological parameters detection system.This system includes hardware acquisition circuit and Android mobile side.The hardware acquisition circuit collects the human body pulse signal through the single-guided photoelectric volume pulse sensor,and makes the simple filtering processing to the signal.The main function of the Android mobile terminal is to display the waveform of the PPG signal,data storage and blood pressure,heart rate,arterial elasticity,microcirculation and other physiological parameters of the calculation display function.