The underlying assumption is that biological systems are complex and exhibit non-linear patterns of activity, and that characterizing that complexity (using dedicated mathematical approaches) is useful to understand, and make inferences and predictions about the system.
The complexity of Heart Rate Variability is a useful predictor of cardiovascular health.
[5] In Python, NeuroKit provides a comprehensive set of functions for complexity analysis of physiological data.
[8] casnet implements a collection of analytic tools for studying signals recorded from complex adaptive systems.
[9] In MATLAB, The Neurophysiological Biomarker Toolbox (NBT) allows the computation of Detrended fluctuation analysis.