The paper investigates the multifractal nature of healthy human heartbeat dynamics and its loss in congestive heart failure. The authors use multifractal analysis, which requires a large number of exponents to characterize the scaling properties of complex signals, to study heartbeat time series. They find that healthy heart rates exhibit multifractal behavior, characterized by a broad range of local Hurst exponents and non-zero fractal dimensions. In contrast, heart rate data from congestive heart failure patients show a clear loss of multifractality, with a linear scaling spectrum and a narrow range of exponents. The multifractal analysis also reveals that healthy heart rates have more anti-correlated behavior compared to heart failure subjects. The study suggests that multifractal analysis can add diagnostic power to contemporary methods of analyzing heartbeat time series and provides insights into the complex control mechanisms of the healthy heart.The paper investigates the multifractal nature of healthy human heartbeat dynamics and its loss in congestive heart failure. The authors use multifractal analysis, which requires a large number of exponents to characterize the scaling properties of complex signals, to study heartbeat time series. They find that healthy heart rates exhibit multifractal behavior, characterized by a broad range of local Hurst exponents and non-zero fractal dimensions. In contrast, heart rate data from congestive heart failure patients show a clear loss of multifractality, with a linear scaling spectrum and a narrow range of exponents. The multifractal analysis also reveals that healthy heart rates have more anti-correlated behavior compared to heart failure subjects. The study suggests that multifractal analysis can add diagnostic power to contemporary methods of analyzing heartbeat time series and provides insights into the complex control mechanisms of the healthy heart.