  Disruptions in the normal rhythmic functioning of the heart, termed as
arrhythmia, often result from qualitative changes in the excitation dynamics of
the organ. The transitions between different types of arrhythmia are
accompanied by alterations in the spatiotemporal pattern of electrical activity
that can be measured by observing the time-intervals between successive
excitations of different regions of the cardiac tissue. Using biophysically
detailed models of cardiac activity we show that the distribution of these
time-intervals exhibit a systematic change in their skewness during such
dynamical transitions. Further, the leading digits of the normalized intervals
appear to fit Benford's law better at these transition points. This raises the
possibility of using these observations to design a clinical indicator for
identifying changes in the nature of arrhythmia. More importantly, our results
reveal an intriguing relation between the changing skewness of a distribution
and its agreement with Benford's law, both of which have been independently
proposed earlier as indicators of regime shift in dynamical systems.
