Abstract：Objective To use the support vector machine (SVM) to establish a quality control (QC)
model for QC evaluation of noninvasive blood pressure (NIBP). Methods Eighty Mindray monitors
were randomly selected from our hospital. And the blood pressure values under five groups of given
parameters were measured by using Fluke simulator, and 80 x 5 matrix vector was set as input. If the
maximum error between measured values and given values was within the range of 10mmHg, the
monitors were thought as qualified and marked as 1; otherwise, 0 indicated the monitor was unqualified.
The 80 x 1 matrix vector was set as output. 60 sets of data were selected as a training set and a multiinput
single-output classification model was established by using SVM. The remaining twenty samples
was set as a test set to verify whether the method was feasible according to the classification accuracy.
Results The classification accuracy rate of the model was 93.3%. Conclusion The method was feasible
with novel, fast and convenient advantages. SVM could be used in the quality control of NIBP.
徐佳佳. 支持向量机在监护仪无创血压质量控制中的应用研究[J]. 中国医疗设备, 2016, 31(11): 127-128.
XU Jia-jia. Study on the Application of Support Vector Machine in Quality Control
of Non-invasive Blood Pressure. China Medical Devices, 2016, 31(11): 127-128.
