The analysis method of the Hilbert spectrum entropy of dividing frequency range for signals of heart rate variability.
- Author:
Hongsheng DONG
1
;
Aihua ZHANG
;
Tianshuang QIU
;
Xiaohong HAO
Author Information
1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China. shdong712@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electrocardiography;
methods;
Entropy;
Heart Rate;
physiology;
Humans;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2011;28(2):248-254
- CountryChina
- Language:Chinese
-
Abstract:
The signal analysis of heart rate variability (HRV) has been very significant for heart disease of aided diagnosis, monitoring and evaluation. We proposed a new method of HRV signal analysis based on the Hilbert spectrum entropy dividing frequency range. According to Hilbert spectrum characteristics of the multi-resolution and the characteristic of HRV signal frequency spectrum, the Hilbert time-frequency spectrum entropy of HRV signal in different frequency range and the full frequency Hilbert time-frequency spectrum entropy with weighting factor were calculated. This approach was analyzed after the appropriate separation for various physiological factors based on the frequency range and it is more conducive to reflect the physiological and the pathological characteristics. Applying the new approach to the actual HRV signal of the MIT-BIH standard database, we obtained the results which showed that this method could effectively differentiate from the sample group for the young, the elder and the patients with atrial fibrillation, and for the sample group for the healthy persons and CHF patients, the performance in statistical analysis was superior to those of the general time-frequency entropy method. The approach could provide an effective analysis method for clinical HRV signal.
