Tang Qingfeng, Xu Shoujiang, Guo Mengjuan, Wang Guangjun, Pan Zhigeng, Su Benyue
The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, 1318 Jixian North Road, Anqing, 246133 China.
School of Public Health, Hangzhou Normal University, 2318 Yuhangtang Road, Hangzhou, 311121 China.
Health Inf Sci Syst. 2022 Apr 21;10(1):7. doi: 10.1007/s13755-022-00172-0. eCollection 2022 Dec.
Vascular age (VA) is the direct index to reflect vascular aging, so it plays a particular role in public health. How to obtain VA conveniently and cheaply has always been a research hotspot. This study proposes a new method to evaluate VA with wrist pulse signal.
Firstly, we fit the pulse signal by mixed Gaussian model (MGM) to extract the shape features, and adopt principal component analysis (PCA) to optimize the dimension of the shape features. Secondly, the principal components and chronological age (CA) are respectively taken as the independent variables and dependent variable to establish support vector regression (SVR) model. Thirdly, the principal components are fed into the SVR model to predicted the vascular aging of each subject. The predicted value is regarded as the description of VA. Finally, we compare the correlation coefficients of VA with pulse width (PW), inflection point area ratio (IPA), Ratio b/a (RBA), augmentation index (AIx), diastolic augmentation index (DAI) and pulse transit time (PTT) with those of CA with these six indices.
Compared with the CA, the VA is closer to PW ( = 0.539, < 0.001 to = 0.589, < 0.001 in men; = 0.325, < 0.001 to = 0.400, < 0.001 in women), IPA ( = - 0.446, < 0.001 to = - 0.534, < 0.001 in men; = - 0.623, < 0.001 to = - 0.660, < 0.001 in women), RBA ( = 0.328, < 0.001 to = 0.371, < 0.001 in women), AIx ( = 0.659, < 0.001 to = 0.738, < 0.001 in men; = 0.547, < 0.001 to = 0.573, < 0.001 in women), DAI ( = 0.517, < 0.001 to = 0.532, < 0.001 in men; = 0.507, < 0.001 to = 0.570, < 0.001 in women) and PTT ( = 0.526, < 0.001 to = 0.659, < 0.001 in men; = 0.577, < 0.001 to = 0.814, < 0.001 in women).
The VA is more representative of vascular aging than CA. The method presented in this study provides a new way to directly and objectively assess vascular aging in public health.
血管年龄（VA）是反映血管老化的直接指标，在公共卫生中具有特殊作用。如何方便且低成本地获取血管年龄一直是研究热点。本研究提出一种利用腕部脉搏信号评估血管年龄的新方法。
首先，用混合高斯模型（MGM）拟合脉搏信号以提取形态特征，并采用主成分分析（PCA）优化形态特征的维度。其次，将主成分和实际年龄（CA）分别作为自变量和因变量建立支持向量回归（SVR）模型。第三，将主成分输入SVR模型预测每个受试者的血管老化情况。预测值被视为血管年龄的描述。最后，比较血管年龄与脉搏宽度（PW）、拐点面积比（IPA）、b/a比值（RBA）、增强指数（AIx）、舒张期增强指数（DAI）和脉搏传播时间（PTT）的相关系数与实际年龄与这六个指标的相关系数。
与实际年龄相比，血管年龄与脉搏宽度（男性中r = 0.539，P < 0.001至r = 0.589，P < 0.001；女性中r = 0.325，P < 0.001至r = 0.400，P < 0.001）、拐点面积比（男性中r = - 0.446，P < 0.001至r = - 0.534，P < 0.001；女性中r = - 0.623，P < 0.001至r = - 0.660，P < 0.001）、b/a比值（女性中r = 0.328，P < 0.001至r = 0.371，P < 0.001）、增强指数（男性中r = 0.659，P < 0.001至r = 0.738，P < 0.001；女性中r = 0.547，P < 0.001至r = 0.573，P < 0.001）、舒张期增强指数（男性中r = 0.517，P < 0.001至r = 0.532，P < 0.001；女性中r =
