Abstract:Objective To find the correlation among the discrete quality control data of a multi-parameter monitor, by establishing
the autoregressive integrated moving average (ARIMA) model, so that the performance variation of the equipment can be
predicted. Methods The attributes of the quality control data of the monitor was fully studied. ARIMA model and SPSS statistical
tools were used to determine model parameters, and the temporal series were predicted in the short term. Results By means of
parameter calculation, the optimal fitting model and estimate trend curve were obtained, which conformed to the characteristics of
time sequence. The maximum absolute error between the actual value and that of the simulated prediction was 1.31%, accurately
predicting the performance of SpO2 related circuits. Conclusion The experimental result has shown that the ARIMA model is
capable of simulating the quality and performance trend of circuits related to SpO2. The model is able to describe equipment status in
a timely manner, which has guiding significance for the preventative maintenance of medical equipment.
宗伟,姜宏涛,王明刚. 基于ARIMA模型监护仪质控数据性能预测的研究[J]. 中国医疗设备, 2022, 37(1): 118-121.
ZONG Wei, JIANG Hongtao, WANG Minggang. Research on Performance Prediction of Monitor Quality Control Based on ARIMA Model. China Medical Devices, 2022, 37(1): 118-121.