Research of Blood Glucose Control State Detection Based on Percussion Entropy
XIAO Ming-xia1,2,LU Chang-hua1,NA Ta2,WANG Tao1
1. School of Computer and Information, Hefei University of Technology, Hefei, Anhui 230601, China
2. School of Electrical and Information Engineering, North Minzu University, Yinchuan, Ningxia 750021, China
Abstract：Aiming at the limitations of existing models of blood glucose control state analysis, an algorithm of blood glucose control state analysis based on percussion entropy (PEn) was proposed.The human pulse wave and ECG signal were collected non-invasively. The amplitude characteristics of the pulse wave signal and the time interval characteristics of the R wave cycle of the ECG signal were extracted to form two time-synchronized numerical sequences. Compared the change trends of the two sequences, calculate the collision entropy of the pulse wave and the ECG signal, and finally detect the blood glucose control status. The results showed that the difference of PEn between healthy and well-controlled diabetic patients was p=0.014, while that between well-controlled and poorly-controlled diabetic patients was p=0.002.From the impact of HbA1c on the two indicators, the PEn index was 30.5% higher than the index of fEmax_RF.PEn can not only been used to reflect the prevalence of diabetes mellitus, but also showed good differences in glycemic control.
肖明霞,鲁昌华,塔娜,王涛. 基于脉搏心电信号碰撞熵的血糖控制状态检测研究[J]. 计量学报, 2023, 44(4): 657-663.
XIAO Ming-xia,LU Chang-hua,NA Ta,WANG Tao. Research of Blood Glucose Control State Detection Based on Percussion Entropy. Acta Metrologica Sinica, 2023, 44(4): 657-663.
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2023, Vol. 44 
