Research On Human Pulse Wave Blood Pressure Detection System Based On FBG

The pulse wave is produced by the human heart pumping blood regularly and propagating along the blood vessels.Its strength changes can fully reflect the condition of the blood vessels.Therefore,studying the characteristic parameters of pulse waves can provide references for the prevention and treatment of vascular diseases.At present,in the field of pulse wave detection at home and abroad,piezoelectric,photoelectric,bioelectrical impedance and other sensors are widely used.The detection principle is basically converted from electrical signals.Therefore,it will inevitably be affected in special medical environments.Affected by electromagnetic interference,it is not conducive to signal detection.This paper first selects PDMS materials for packaging protection in the manufacture of FBG pulse wave sensors,and uses COMSOL simulation to study the influence of substrate thickness and sensor placement on the strain transfer performance.The experimental results show that increasing the thickness of the substrate and the closer the sensor is to the load surface,the greater the stress amplitude and the better the transmission effect.The conclusion is that the package size is finally determined.Then three methods of wavelet analysis,morphology,and ensemble empirical mode decomposition are used to preprocess the measured pulse signal.And three denoising evaluation indicators are proposed: wave balance coefficient(WBC),signal-to-noise ratio(SNR)and root mean square error(RMSE),and the shortcomings of each method are analyzed.Finally,this article is based on EEMD decomposition.Combined with the curve fitting method,the low-frequency baseline signal in the signal is completely removed,so as to achieve the best preprocessing effect.Finally,this paper combines the curve fitting method on the basis of EEMD decomposition to achieve the complete removal of the low-frequency baseline signal in the signal,so that the preprocessing effect is optimal.Secondly,in terms of pulse wave feature extraction,for four types of pulse waves,this article combines the differential signal to propose a time-domain differential period ratio(TDDR)algorithm,which the accuracy of each feature point recognition is improved..The results show that the identification accuracy of the starting point and peak point of pulse wave can reach 100% within the allowable error range after preprocessing the collected data.In the resting state,the recognition accuracy of the tidal wave d and e points It is 98.28% and 97.25%,and the recognition accuracy of points f and g of the dicrotic wave is 98.14% and 99.19%.In the exercise state,the recognition accuracy of tidal wave d and e are 94.23% and 90.77%,respectively.The recognition accuracy rates of f and g are 91.93% and 95.38% respectively.Finally,the maximum errors of systolic pressure Sp and diastolic blood pressure Dp estimated linearly according to the characteristic parameters are 7.7mm Hg and 3.67 mm Hg respectively,which meet the standard requirements,and use MATLAB to build a blood pressure monitoring platform based on FBG pulse wave to realize FBG pulse wave signal preprocessing.,Feature extraction and blood pressure calculation.