Research On Cardiovascular Physiological Parameters Monitoring System

According to the World Health Organization,cardiovascular disease(CVD)has become the leading cause of death worldwide.In China,the number of people suffering from cardiovascular diseases continues to grow,with approximately 290 million patients.The physiological and pathological information of human body is the basis for determining the severity of disease and the diagnosis of disease,and is an important vital sign of human body.Blood oxygen saturation?blood pressure and heart rate is very important human physiological parameters,can reflect the status of cardiovascular function.The real-time noninvasive detection of these physiological parameters can avoid the occurrence of cardiovascular diseases and other accidents to a certain extent.The photoplethysmography contains a large number of physiological and pathological information such as blood pressure?blood oxygen saturation?blood flow?blood glucose?respiration rate and so on.Therefore,the detection of the change of pulse waveform characteristics can be achieved noninvasive detection of cardiovascular physiological parameters.In order to extract the characteristic parameters from the photoplethysmography,calculating the blood pressure,blood oxygen saturation and heart rate,the pulse wave signal is collected and denoised and the corresponding algorithm is studied in this thesis.Firstly,a pulse wave hardware acquisition system is designed and built.The hardware mainly includes the light source drive module,the photoelectric receiving module amplifier module etc.,realizing the acquisition and preprocessing and storage of the pulse wave.Analyzing and studying the characteristics of photoplethysmography and noise sources,wavelet thresholding algorithm is adopted to the initial pulse wave signal based on sym8 wavelet in this thesis The wavelet transform was used to remove the baseline drifting of the pulse wave signal,and the wavelet base of sym8 was selected.The pulse wave was decomposed by 9 layers,and the baseline was removed from the pulse wave signal,and the better effect was obtained.To remove the noise and baseline of pulse wave,a continuous wavelet transform is used to identify characteristic point of the pulse wave.Then,the regression equation of pulse parameters and systolic pressure?diastolic blood pressure was established by stepwise regression method,realizing measure blood pressure by characteristic parameters of the pulse wave.Secondly establishing dual wavelength pulse wave oxygen saturation model based Lambert-Beer Law,finding the photoplethysmography peak?valley value and calculating the R value,combined with oxygen saturation reference fitting model of blood oxygen saturation,blood oxygen saturation is calculated.Finally,the frequency domain Fast Fourier Transform algorithm is used to analyze the photoplethysmography in the frequency domain to determine the heart rate.In this thesis,the blood pressure?blood oxygen saturation and heart rate is compared with the measured values,and the results show that the algorithm is feasible in this thesis.The calculation results have high stability accuracy.