OBJECTIVE: To show that the pulse diagnosis used in Traditional Chinese Medicine, combined with nonlinear dynamic analysis, can help identify car- diovascular diseases. METHODS: Recurrence quantification analysis (...OBJECTIVE: To show that the pulse diagnosis used in Traditional Chinese Medicine, combined with nonlinear dynamic analysis, can help identify car- diovascular diseases. METHODS: Recurrence quantification analysis (RQA) was used to study pulse morphological changes in 37 inpatients with coronary heart dis- ease (CHD) and 37 normal subjects (controls). An in- dependent sample t-test detected significant differ- ences in RQA measures of their pulses. A support vector machine (SVM) classified the groups accord- ing to their RQA measures. Classic time-domain pa- rameters were used for comparison. RESULTS: RQA measures can be divided into two groups. One group of measures [ecurrence rate(RR), determinism (DEL), average diagonal line length (L), maximum length of diagonal structures (Lmax), Shannon entropy of the frequency distribu- tion of diagonal line lengths (ENTR), laminarity (LAM), average length of vertical structures (TT), maximum length of vertical structures (Vmax)] showed significantly higher values for patients with CHD than for normal subjects (P〈0.0S). The other measures (RR_std, L_std, Lmaxstd, TT_std, Vmax_std) showed significantly lower values for the CHD group than for normal subjects (P〈0.05). SVM classification accuracy was higher with RQA measures: With RQA (16 parameters) accuracy was at 88.21%, and with RQA(12 parameters) accuracy was at 84.11%. In contrast, with classic time-do- main (15 parameters) accuracy was 75.73%, and with time-domain (7 parameters) accuracy was 74.7O%. CONCLUSION: Nonlinear dynamic methods such as RQA can be used to study functional and struc- tural changes in the pulse noninvasively. Pulse sig- nals of individuals with CHD have greater regulari- ty, determinism, and stability than normal subjects, and their pulse morphology displays less variabili- ty. RQA can distinguish the CHD pulse from the healthy pulse with an accuracy of 88.21%, thereby providing an early diagnosis of cardiovascular dis- eases such as CHD.展开更多
基金Supported by Innovation Program of Shanghai Municipal Education Commission(No.11YZ71)the 3rd Shanghai Leading Academic Discipline Project(No.S30302)the National Natural Science Foundation of China(No. 81173199)
文摘OBJECTIVE: To show that the pulse diagnosis used in Traditional Chinese Medicine, combined with nonlinear dynamic analysis, can help identify car- diovascular diseases. METHODS: Recurrence quantification analysis (RQA) was used to study pulse morphological changes in 37 inpatients with coronary heart dis- ease (CHD) and 37 normal subjects (controls). An in- dependent sample t-test detected significant differ- ences in RQA measures of their pulses. A support vector machine (SVM) classified the groups accord- ing to their RQA measures. Classic time-domain pa- rameters were used for comparison. RESULTS: RQA measures can be divided into two groups. One group of measures [ecurrence rate(RR), determinism (DEL), average diagonal line length (L), maximum length of diagonal structures (Lmax), Shannon entropy of the frequency distribu- tion of diagonal line lengths (ENTR), laminarity (LAM), average length of vertical structures (TT), maximum length of vertical structures (Vmax)] showed significantly higher values for patients with CHD than for normal subjects (P〈0.0S). The other measures (RR_std, L_std, Lmaxstd, TT_std, Vmax_std) showed significantly lower values for the CHD group than for normal subjects (P〈0.05). SVM classification accuracy was higher with RQA measures: With RQA (16 parameters) accuracy was at 88.21%, and with RQA(12 parameters) accuracy was at 84.11%. In contrast, with classic time-do- main (15 parameters) accuracy was 75.73%, and with time-domain (7 parameters) accuracy was 74.7O%. CONCLUSION: Nonlinear dynamic methods such as RQA can be used to study functional and struc- tural changes in the pulse noninvasively. Pulse sig- nals of individuals with CHD have greater regulari- ty, determinism, and stability than normal subjects, and their pulse morphology displays less variabili- ty. RQA can distinguish the CHD pulse from the healthy pulse with an accuracy of 88.21%, thereby providing an early diagnosis of cardiovascular dis- eases such as CHD.