Key result
The combination of transfer entropy indices derived from empirical mode decomposition and LF/HF achieved a congestive heart failure screening accuracy of 85.7%, compared to 79.6% with LF/HF alone.
Why the study?
Congestive heart failure is related to autonomic nervous system dysfunction and fragmented patterns, driving a growing demand for accurate assessment.
Does Empirical Mode Decomposition combined with transfer entropy improve the accuracy of congestive heart failure screening compared to traditional LF/HF ratio?
Case-Control (n=98)
Does Empirical Mode Decomposition combined with transfer entropy improve the accuracy of congestive heart failure screening compared to traditional LF/HF ratio?
Absolute Event Rate: 85.7% vs 79.6%
The combination of Empirical Mode Decomposition-derived transfer entropy indices and LF/HF improves the accuracy of congestive heart failure screening from 24-hour RR interval signals.
Congestive heart failure (CHF) is a cardiovascular disease related to autonomic nervous system (ANS) dysfunction and fragmented patterns. There is a growing demand for assessing CHF accurately. In this work, 24-h RR interval signals (the time elapsed between two successive R waves of the QRS signal on the electrocardiogram) of 98 subjects (54 healthy and 44 CHF subjects) were analyzed. Empirical mode decomposition (EMD) was chosen to decompose RR interval signals into four intrinsic mode functions (IMFs). Then transfer entropy (TE) was employed to study the information transaction among four IMFs. Compared with the normal group, significant decrease in TE (*→1; information transferring from other IMFs to IMF1, p < 0.001) and TE (3→*; information transferring from IMF3 to other IMFs, p < 0.05) was observed. Moreover, the combination of TE (*→1), TE (3→*) and LF/HF reached the highest CHF screening accuracy (85.7%) in IBM SPSS Statistics discriminant analysis, while LF/HF only achieved 79.6%. This novel method and indices could serve as a new way to assessing CHF and studying the interaction of the physiological phenomena. Simulation examples and transfer entropy applications are provided to demonstrate the effectiveness of the proposed EMD decomposition method in assessing CHF.
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Chen et al. (2019) conducted a case-control in Congestive heart failure (n=98). Combination of transfer entropy (TE) indices and LF/HF vs. LF/HF alone was evaluated on Congestive heart failure screening accuracy. The combination of transfer entropy indices derived from empirical mode decomposition and LF/HF achieved a congestive heart failure screening accuracy of 85.7%, compared to 79.6% with LF/HF alone.
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