Time–frequency distribution of heart rate variability below 0.05Hz by Wigner–Ville spectral analysis in congestive heart failure patients

BACKGROUND: Heart rate variability reflects autonomic tone and is used to assess progression and prognosis in a variety of illnesses. However, multiple heart rate variability methods exist and are not necessarily equivalent. OBJECTIVES: To compare four methods of heart rate variability in heart failure patients and healthy subjects. METHODS: Twenty-four-hour Holter recordings were obtained in 50 heart failure patients and 50 age- and gender-matched control patients. From these recordings, heart rate variability was assessed by histograms, standard deviation, Poincare plots, and spectral analysis. RESULTS: For R-R interval histograms, standard deviation, and Poincare plots, diminished heart rate variability was identified in 65% to 100% of heart failure patients versus 0% to 8% of controls. Agreement among these tests ranged from 69% to 96%. Spectral values varied greatly over the recording period, even in the same subject, possibly because of variations in activity. Only 16% of heart failure patients had spectral values that were identified as abnormal. Agreement between spectral analysis and the other methods ranged between 58% and 67%. CONCLUSIONS: Heart rate variability assessed over a 24-hour period with different techniques yields similar but not identical results. Heart rate variability assessed from spectral analysis of short periods of data varied markedly in a 24-hour period and should not be compared with measures obtained from 24-hour methods. Standardization of subject activity and recording time is necessary for comparison of spectral analysis of brief periods. Further research is required to determine if differences among methods assessing 24-hour heart rate variability yield complementary information.

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USING DIFFERENT ENTROPIES TO ANALYZE THE HEART RATE VARIABILITY OF CONGESTIVE HEART FAILURE PATIENTS

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237211002530 ◽

2011 ◽

Vol 23 (04) ◽

pp. 253-260 ◽

Cited By ~ 2

Author(s):

Ren-Guey Lee ◽

Chun-Chieh Hsiao ◽

Chieh-Yi Kao

Keyword(s):

Heart Failure ◽

Heart Rate ◽

Congestive Heart Failure ◽

Heart Rate Variability ◽

Analysis Of Variance ◽

Human Body ◽

Approximate Entropy ◽

Young Group ◽

Multiscale Entropy ◽

Heart Failure Patients

The purpose of this paper is to show the influence of congestive heart failure (CHF) on heart by using different entropies to apply on the group of patients with CHF and normal group. Three different entropies are used: approximate entropy (ApEn), multiscale entropy (MSE), and base-scale entropy (BsEn). We use these three entropies to measure the complexity of the heart rate variability (HRV) and also use analysis of variance (ANOVA) to analyze the result of entropies to discuss the feasibility of recognizing CHF patients by utilizing entropies. With the analysis results of different entropies, the influence of CHF on heart has also been clearly demonstrated. The results on the approximate entropy show that the normal young group has a higher approximate entropy value while the CHF group has a lower value. This can be explained as a healthy, strong heart that can change its heart rate freely to adapt the change of the environment or the needs of the human body, therefore the HRV will be more complex. From the ANOVA results of approximate entropy, it can be observed that the F value is larger than 1, but is still small. In other words, the approximate entropy can be used to distinguish the three groups, the effect is, however, not good. It is hard to recognize a CHF patient by using approximate entropy.

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