  We propose a metric to characterize the complex behavior of a dynamical
system and to distinguish between organized and disorganized complexity. The
approach combines two quantities that separately assess the degree of
unpredictability of the dynamics and the lack of describability of the
structure in the Poincar\'e plane constructed from a given time series. As for
the former, we use the permutation entropy $S_{\rm p}$, while for the later, we
introduce an indicator, the {\em structurality} $\Delta$, which accounts for
the fraction of visited points in the Poincar\'e plane. The complexity measure
thus defined as the sum of those two components is validated by classifying in
the ($S_{\rm p}$,$\Delta$) space the complexity of several benchmark
dissipative and conservative dynamical systems. As an application, we show how
the metric can be used as a powerful biomarker for different cardiac
pathologies and to distinguish the dynamical complexity of two electrochemical
dissolutions.
