Regular heartbeat dynamics are associated with cardiac health.

The human heartbeat series is more variable and, hence, more complex in healthy subjects than in congestive heart failure (CHF) patients. However, little is known about the complexity of the heart rate variations on a beat-to-beat basis. We present an analysis based on symbolic dynamics that focuses on the dynamic features of such beat-to-beat variations on a small time scale. The sequence of acceleration and deceleration of eight successive heartbeats is represented by a binary sequence consisting of ones and zeros. The regularity of such binary patterns is quantified using approximate entropy (ApEn). Holter electrocardiograms from 30 healthy subjects, 15 patients with CHF, and their surrogate data were analyzed with respect to the regularity of such binary sequences. The results are compared with spectral analysis and ApEn of heart rate variability. Counterintuitively, healthy subjects show a large amount of regular beat-to-beat patterns in addition to a considerable amount of irregular patterns. CHF patients show a predominance of one regular beat-to-beat pattern (alternation of acceleration and deceleration), as well as some irregular patterns similar to the patterns observed in the surrogate data. In healthy subjects, regular beat-to-beat patterns reflect the physiological adaptation to different activities, i.e., sympathetic modulation, whereas irregular patterns may arise from parasympathetic modulation. The patterns observed in CHF patients indicate a largely reduced influence of the autonomic nervous system. In conclusion, analysis of short beat-to-beat patterns with respect to regularity leads to a considerable increase of information compared with spectral analysis or ApEn of heart-rate variations.