Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment

摘要: In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV useful tool assessment. The multi-frequency components Entropy (MFC-En), which obtained by Hilbert-Huang transform entropy algorithm, was proposed as analyzing CHF. This paper included 24-h signals of 98 subjects collected Holter (54 healthy, 12 low-risk CHF, 32 high-risk subjects). MFC-En successfully showed statistical significance between control groups (p <; 0.001). classification accuracy 86.7%, while ratio lowand high-frequency power only 79.6%. Moreover, significances found among control, 0.01). Therefore, revealed patient more activated measuring complexity rhythms changes throughout day.