Characterization of Congestive Heart Failure by the Pattern of Diurnal Rhythm Based on Heart Rate Variability

The impaired autonomic nervous system(ANS)has a close relationship to morbidity and mortality for congestive heart failure(CHF).This study is aimed to investigate the possibility to characterize CHF by the pattern of diurnal rhythm based on heart rate variability(HRV).Two datasets of CHF(n=44)were from PhysioNet.And the datasets of the normal from THEW(n=189).Two 2 h episodes representing day and night in resting state were selected in each Holter record.Measures concerning time domain,AR model-based analysis,symbol dynamic analysis,and non-Gaussian indexes(λ)were calculated in each episode.The diurnal rhythm was represented by the ratio of an index in the day to that at night.Results demonstrated different patterns of diurnal rhythm among the normal,mild CHF(NYHAI-Ⅱ)and severe CHF(NYHA Ⅲ-Ⅳ),reflecting the changes in sympathetic and vagal interaction from reciprocal function to accentuated antagonism due to CHF.Furthermore,using RRIn,(LFnu)d/(LFnu)n and λd/λn,the sensitivity and specificity for discriminating the normal and CHF reached 95.45％and 95.24％;And for discriminating between mild CHF and severe CHF were 84.38％and 91.67％.Our proposed method is promising in assessing the ANS state and monitoring therapeutic effects for CHF patients.