今天是:   返回主页   |   加入收藏   |   联系我们
引用本文:
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  下载PDF阅读器  关闭
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 20次   下载 11 本文二维码信息
码上扫一扫!
分享到: 微信 更多
阴虚质健康人群脉诊特征分析
向灵希1, 汪南玥1,2, 刘佳2
1.陕西中医药大学基础医学院, 咸阳 712046;2.中国中医科学院医学实验中心, 北京 100700
摘要:
[目的] 对北京市、天津市、河北省等地区阴虚质、平和质健康人群的脉诊信息特征进行比较、分析,研究两组人群脉诊信息特征的差异性。[方法] 应用三探头中医脉诊仪采集阴虚质133例、平和质153例,共286名受试者双侧寸、关、尺6部脉的脉诊信息,经过滤波去噪后建立12谐波拟合模型,并提取出193个特征参数,使用主成分分析、最小二乘法、套索回归等无监督学习与有监督学习相结合的方法进行数据特征分析,完善北京市、天津市、河北省等地区阴虚质人群脉诊信息判决模型。[结果] 阴虚质与平和质健康人群的脉诊信息差异显著,主成分分析结果可见两组数据在第1、2主成分方面差异显著,最小二乘法与套索回归将两组数据进行区分的准确率达到71%~75%,阴虚质健康人群脉象特征变化在时域参数上表现为除左侧尺脉、右侧寸脉外的脉力(h)1值减小,右侧关脉脉图面积(s)减小和除左侧关脉外的脉内压力水平(w)值均增大。在频域参数上表现为双侧关脉、尺脉变化显著。[结论] 北京市、天津市、河北省等地区阴虚质与平和质健康人群的脉诊信息差异显著,差异主要通过关部和尺部的h1、ws等特征参数体现,与临床阴虚证人群多见细脉、高血压病阴虚证人群多出现弦脉等表现相符。为中医理论“肝肾同源”“金水相生”等观点提供数据支持,也为中医脉诊客观化体质辨识提供客观参考。
关键词:  阴虚质  体质辨识  脉诊信息  特征参数
DOI:10.11656/j.issn.1673-9043.2025.01.03
分类号:R2-03
基金项目:国家重点研发计划项目(CI2018YFC1707605);科技部基础性工作专项项目(CI2013FY114400);中国中医科学院科技创新工程项目(CI2021A05207);北京市中医药科技发展资金项目(CIBJZYQN-2023-03)。
Analysis of pulse diagnosis characteristics in healthy individuals with yin deficiency constitution
XIANG Lingxi1, WANG Nanyue1,2, LIU Jia2
1.College of Basic Medicine, Shaanxi University of Traditional Chinese Medicine, Xianyang 712046, China;2.Medical Experiment Center of China Academy of Chinese Medical Sciences, Beijing 100700, China
Abstract:
[Objective] Comparison and analysis of pulse diagnosis information characteristics of individuals with yin deficiency constitution and balanced constitution in healthy populations in Beijing-Tianjin-Hebei and other cities,studying the differences in pulse diagnosis information characteristics between the two groups. [Methods] Using the three-probe traditional Chinese pulse diagnosis instrument,pulse diagnosis information from the cunguan and chi pulses of 133 individuals with yin deficiency constitution and 153 individuals with balanced constitution were collected,totaling 286 participants. After filtering and noise reduction,12 harmonic fitting models were established for the information,and 193 characteristic parameters were extracted from the pulse diagnosis information of each subject. Unsupervised and supervised learning methods such as principal component analysis,least square estimation,and least absolute shrinkage and selection operator were employed for data feature analysis,improving the decision model for pulse diagnosis information of individuals with yin deficiency constitution in Beijing-Tianjin-Hebei and other cities. [Results] There were significant differences in pulse diagnosis information between the yin deficiency group and the balanced group. The data of the two groups showed significant differences in the first and second principal components in PCA. The accuracy of distinguishing between the two groups using LS and Lasso reached 71% to 75%. The pulse characteristics of individuals with yin deficiency constitution manifested as a decrease in h1 values in all positions except the left chi and right cun,a decrease in s in the right Cuan,and an increase in w values in all positions except the left Cuan. Significant changes in pulse were observed in the frequency domain parameters of both guan and bilateral chi. [Conclusion] There are significant differences in pulse diagnosis information between individuals with yin deficiency constitution and balanced constitution in Beijing-Tianjin-Hebei and other cities,mainly reflected in characteristic parameters such as pulse force(h1),pulse pressure(w),and pulse area(s) at the guan and chi positions. This is consistent with the clinical phenomena of fine pulse in yin deficiency syndrome and string-like pulse in hypertension yin deficiency syndrome. It also provides data support for traditional Chinese medicine(TCM) theories such as “liver and kidney homologous” and “generation between the metal and water”. This also provides objective references for the objective identification of constitution through TCM pulse diagnosis.
Key words:  yin deficiency constitution  constitution identification  pulse diagnosis information  characteristic parameter
关注公众号二维码