School of Electrical and Information Engineering, North Minzu University, Yinchuan, Ningxia, China.
Basic Experimental Teaching and Engineering Training Center, North Minzu University, Yinchuan, Ningxia, China.
Technol Health Care. 2022;30(6):1359-1369. doi: 10.3233/THC-220040.
Arteriosclerosis is one of the diseases that endanger human health. There is a large amount of information in pulse wave signals to reflect the degree of arteriosclerosis.
The degree of arteriosclerosis is assessed by analyzing pulse wave signal and calculating multi-scale entropy values.
A method based on the multiscale cross-approximate entropy of the pulse wave of the human finger is proposed to assess the degree of arteriosclerosis. A total of 86 subjects were divided into three groups. The data of 1000 pulse cycles were selected in the experiment, and the multiscale cross-approximate entropy was calculated for the climb time and pulse wave peak interval. Independent sample t-test analysis gives the small-scale cross-approximate entropy of the two time series of climb time and pulse wave peak interval as p< 0.001 in Groups 1 and 2. The large-scale cross-approximate entropy of the two time series of climb time and pulse wave peak interval is p< 0.017 in Groups 2 and 3.
Using the proposed algorithm, the results showed that the small-scale cross-approximate entropy of climb time and pulse wave peak interval could reflect the degree of arteriosclerosis in the human body from the perspective of autonomic nerve function. The large-scale cross-approximate entropy of climb time and pulse wave peak interval confirmed the effect of diabetes on the degree of arteriosclerosis.
The results demonstrate the multiscale cross-approximate entropy is a comprehensive index to evaluate the degree of human arteriosclerosis.
动脉硬化是危害人类健康的疾病之一。脉搏波信号中包含大量信息，可反映动脉硬化的程度。
通过分析脉搏波信号并计算多尺度熵值来评估动脉硬化程度。
提出了一种基于人体指脉搏波的多尺度交叉近似熵的方法来评估动脉硬化程度。共 86 名受试者分为三组。在实验中选择了 1000 个脉搏周期的数据，并计算了攀登时间和脉搏波峰值间隔的多尺度交叉近似熵。独立样本 t 检验分析表明，在第 1 组和第 2 组中，两个时间序列（攀登时间和脉搏波峰值间隔）的小尺度交叉近似熵 p<0.001。在第 2 组和第 3 组中，两个时间序列（攀登时间和脉搏波峰值间隔）的大尺度交叉近似熵 p<0.017。
使用提出的算法，结果表明，攀登时间和脉搏波峰值间隔的小尺度交叉近似熵可以从自主神经功能的角度反映人体动脉硬化的程度。攀登时间和脉搏波峰值间隔的大尺度交叉近似熵证实了糖尿病对动脉硬化程度的影响。
结果表明，多尺度交叉近似熵是评估人类动脉硬化程度的综合指标。
