| With the increasing pace of life,the widespread unhealthy eating habits,and the aging of the population,the incidence of cardiovascular diseases represented by hypertension is increasing year by year.It seriously endangers people’s life,health,and safety.Hypertension is called the "invisible killer",and its treatment rate and control rate are not high,so timely and accurate blood pressure measurement is particularly important.The accuracy of blood pressure measurement is easily affected by many factors,including the environment,patient emotions,and experimental procedures,and errors are prone to occur.Traditional sphygmomanometers are based on the oscillometric method,which can only display blood pressure values,and the reliability of the measurement results is unknown.To address this situation,this paper proposed a quantitative evaluation algorithm for pulse waveforms in oscillometric blood pressure measurement by processing data from a hardware acquisition system and validating and analyzing it.The main content of the paper is as follows:1.Construction of the hardware acquisition system: In terms of hardware circuitry,this thesis incorporated the pressure sensor used and designed a pulse wave extraction circuit;the pulse wave signal was acquired and processed through the MCU’s AD,and the processed results were saved via the serial port.In this thesis,an upper computer software based on Matlab was designed,through which the blood pressure data can be read and analyzed,and the graphs of the pulse wave and the analysis results can be displayed and saved.The experimental procedure and content were planned in detail,six conditions(one standard condition and five noisy conditions)were designed,and the experimental data were collated.2.A blood pressure value determination algorithm based on the oscillometric method was proposed: a suitable pulse wave signal was extracted from it by high-pass filtering of the cuff pressure and by wavelet threshold denoising.Its peak points were accurately identified by a combination of the threshold and extreme value methods.After comparing the fitting parameters of various algorithms,the Gaussian fitting was finally determined for the envelope on the pulse wave.Based on the fitted curve and the variable amplitude coefficient method,the systolic and diastolic pressures were finally determined.3.Quantitative evaluation and classification of blood pressure data: The extracted pulse wave was further processed to remove the trend.At the same time,the Gaussian fitting was optimized,and an index for evaluating the stability of pulse wave waveform—quality index was proposed according to the fitting effect.Quality index and blood pressure errors were sorted,and the classification boundaries were defined by linear SVM.In this paper,the quality of pulse wave was divided into four categories from high to bottom,namely A,B,C,D.A: quality index<0.14;B: 0.14≤quality index<0.28;C: 0.28≤quality index<0.48;D: quality index ≥ 0.48.4.The experimental results were validated and the data were analyzed: the standard conditions in this thesis and the reference Omron sphygmomanometer were analyzed for consistency.For the systolic blood pressure,the mean value was-0.2209 mm Hg,and the standard deviation was 1.8938 mm Hg;the mean value of diastolic blood pressure was 0.9406 mm Hg,and the standard deviation was 1.5145 mm Hg,all of which meet the standards of AAMI/ISO and have strong consistency.In addition,for five noise conditions,this thesis quantifies the influence of each condition on blood pressure values and the significance between them and the standard condition.Finally,the reliability of the classification results was verified,and the algorithm was ported to a host computer to enable the quality assessment of blood pressure data. |
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