[Study of traditional Chinese medicine pulse signals in patients with coronary heart disease based on recurrence quantification analysis]

Zhong Xi Yi Jie He Xue Bao. 2011 Nov;9(11):1226-33. doi: 10.3736/jcim20111111.
[Article in Chinese]

Abstract

Objective: By using recurrence quantification analysis (RQA) to analyze traditional Chinese medicine pulse signals of patients with coronary heart disease (CHD), this study aims to find nonlinear dynamic parameters of pulses to distinguish patients with CHD from normal subjects.

Methods: First, pulse signals were collected using ZBOX-I pulse digitization gathering analyzer from October 2007 to June 2008. RQA was used to analyze RQA parameters of pulses of 63 patients with CHD and 61 normal subjects. RQA parameters included recurrence rate (RR), determinism (DET), averaged diagonal length (L), entropy of diagonal length (ENTR), length of longest diagonal line (L(max)), laminarity (LAM), trapping time (TT) and length of longest vertical line (V(max)). Then, rank-sum test and BoxPlot were employed to find significant difference and distribution of RQA parameters. Lastly, receiver operating characteristic (ROC) curves were used to assess the diagnostic value of the measurements with significant difference.

Results: There were significant differences in RQA parameters of pulse signals between the two groups, including RR, DET, L, ENTR, LAM, TT and V(max), and their areas under the ROC curves were 1.000, 0.898, 0.653, 0.673, 0.885, 0.898, 0.986 and 0.994, respectively.

Conclusion: Compared with the normal subjects, the pulse signals of the patients with CHD are presented with more certainty, regularity and stability. RQA measurements of RR, TT, Vmax, DET and LAM show good diagnostic value according to their ROC curves.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Cardiovascular Physiological Phenomena
  • Case-Control Studies
  • Coronary Disease / diagnosis*
  • Humans
  • Medicine, Chinese Traditional / methods*
  • Middle Aged
  • Pulse
  • ROC Curve