Many natural phenomena behave in a chaotic way, and the classical linear analytical methods don't allow a reliable detection of interdependency among simultaneous measurements of different variables. Hence new analytical methods based on Lorenz system have been developed, in order to reveal non-linear interaction among those variables.

    This is especially interesting in the case of physiological monitoring, where signals are correlated with one another by feedback mechanisms. Cardiorespiratory interaction -interdependency between heart rate and respiration rhytms- is one example where traditional linear tools have been used in order to gain information about its underlying dynamics. In physiological conditions the power spectrum of the heart rate contains a peek centered at the respiratory frequency. In pathological conditions the classical tools, like the power spectrum, may show no signs of interaction. As a consequence the use of a technique aimed to detect hidden frequencies in times series may show an interdependance cardiac and respiratory signals even in pathological conditions.