Study on Improving the Calculation Accuracy of Sphygmomanometer Based on Bidirectional Filtering

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Abstract: Objective: the current market there are all kinds of blood pressure, they use the different filtering algorithm, so its calculation accuracy also are different , through research,determining a sphygmomanometer calculation accuracy of filtering algorithm can be effectively improved. Through the experimental data obtained through different filter algorithm processing data from data comparison with bidirectional filter algorithm gains, studies have shown that the bidirectional filter algorithm to improve the blood pressure cuff on calculation accuracy.

Key Words: Sphygmomanometer, Calculation accuracy of meter, Bidirectional digital filtering


As we all know, high blood pressure is an important cause of heart failure in humans, and it also threatens the life and health of patients. Therefore, accurate measurement of blood pressure has important clinical significance. Generally, electronic sphygmomanometers use oscillometric methods. Generally, data obtained by oscillometric method must be filtered to eliminate noise and filtering interference, so that the measurement data is as accurate as possible. Currently popular filtering algorithms include interpolation filtering, median filtering, bidirectional filtering, and Gaussian filtering. We choose the interpolation filtering method and the median filtering method to compare with the bidirectional filtering algorithm. Study the advantages of the bidirectional filtering algorithm and improve the accuracy of the sphygmomanometer calculation.

The diagramof blood pressure measurement is shown in Fig. 1. In the figure, Ps corresponds to systolic pressure, Pd corresponds to diastolic pressure, and Pm corresponds to average pressure.

Figure 1 shows the principle of blood pressure measurement by wave method

A bidirectional filter (also known as a filter), also known as a bilateral filter, is a nonlinear filtering method in which the image space is close to a combination of compromises and similar pixels, taking into account spatial information and grayscale similarity. The purpose of protection and denoising has been achieved [3]. It is simple, non-linear and non-comprehensive.It is a Gaussian filter function based on spatial distribution, so data far from the edge of gray does not affect the edge. Pixel values, the pixels at the edges are hardly blurred, which serves as a protection boundary and achieves a relatively ideal filtering effect [8].

The systolic pressure algorithm is as in Equation 2-1:Ps=P/Vi=Ks*Um The diastolic pressure algorithm is as in Equation 2-2:Pd=P/Vi=Kd*Um

Materials and Methods

Data from the subjects with different physiological conditions were used as the original data source during the internship using the Beijing Yueqi ABP-1000S sphygmomanometer, and then the data of 10 subjects using the mercury sphygmomanometer were actual data; the original data was interpolated. . The following table data obtained by the filtering method, the median filtering method and the bidirectional filtering method.

The actual data, the measured data, and the measured data processed by the two-way filtering algorithm and the interpolation filtering algorithm median filtering algorithm should be made an intuitive comparison. The actual data is the data measured by the mercury sphygmomanometer. The measured data is the data without any algorithm. DBP stands for diastolic blood pressure, and SBP stands for systolic blood pressure, as shown in Table 1 and Table 2 below:

Calculate the difference between the 20 sets of measured values in the above two tables, and the difference between the blood pressure data obtained by the interpolation filtering algorithm, the median filtering algorithm, and the bidirectional filtering algorithm and the actual blood pressure values (systolic and diastolic), respectively, A, B, C, comparing these three values, the following results are calculated: A = 30, B = 71, C = 68.

It can be seen intuitively that after the blood pressure data processed by the three filtering algorithms, the blood pressure value obtained by the bidirectional filtering process is closest to the actual value, and the error is significantly reduced by the bidirectional filtering algorithm. In summary, we can determine that the two-way Compared with the median and interpolation filtering algorithm, the filtering algorithm has obvious advantages in improving the calculation accuracy of the sphygmomanometer, and can greatly improve the calculation accuracy of the sphygmomanometer.

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Study on Improving the Calculation Accuracy of Sphygmomanometer Based on Bidirectional Filtering. (2019, Mar 20). Retrieved from

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