The study of the pulse signals of atherosclerosis based on Hilbert-Huang transform and sample entropy.
- Author:
Cheng YANG
1
;
Xuemin WANG
;
Tao SUN
;
Hongqiang YU
;
Xiang LI
;
Peng ZHOU
Author Information
1. School of Precision Instruments and Opto-Electronics, Tianjin University, Tianjin 300072, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Atherosclerosis;
diagnosis;
Humans;
Models, Biological;
Pulse;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2012;29(6):1178-1183
- CountryChina
- Language:Chinese
-
Abstract:
Atherosclerosis, one of the serious cardiovascular diseases, is very harmful to human bodies. The early diagnosis of arteriosclerosis is of great significance. In this paper, we collected pulse from healthy adults and patients with atherosclerosis. Using Hilbert-Huang Transform (HHT) and sample entropy, we analyzed the pulse and found the differences between the patients and healthy people. After using the empirical mode decomposition (EMD) to process pulse signals, we calculated sample entropy for each intrinsic mode function (IMF), and did statistical analysis of the IMF. The sample entropy of a first IMF from patients with atherosclerosis is less than that from healthy persons, and there was significant differences between the healthy and patient groups. In calculating the energy value of different frequencies on the HHT marginal spectrum, we found the energy in patients moved to low frequencies obviously. The energy value of frequency between 0-1 Hz was significantly higher in patients than in the healthy group. The t test also showed that the values between the two groups had significant differences. The statistics and figures showed that early diagnosis was feasible based on HHT and sample entropy.
