We introduce a segmentation algorithm to probe the temporal organization of
heterogeneities in human heartbeat interval time series. We find that the
lengths of segments with different local mean heart rates follow a power-la
w distribution and show that this scale-invariant structure is not a simple
consequence of the long-range correlations present in the data. The differ
ences in mean heart rates between consecutive segments display a common fun
ctional form, but with different parameters for healthy individuals and for
heart-failure patients. These findings suggest that there is relevant phys
iological information hidden in the heterogeneities of the heartbeat time s
eries.