A new approach to wavelet entropy: Application to postural signals

Abstract

This study proposes a new approach for quantifying complexity of physiological signals characterized by a spectral distribution in modes. Our approach is inspired by wavelet entropy but based on a modal representation: Synchrosqueezing transform. It is calculated for each time sample within the cone of influence of the decomposition. This index is first validated and discussed on simulated multicomponent signals. Finally, it is applied to assess postural control and ability at using all the sensory resources available. Results show significant differences in our index following an induced change in sensory conditions whereas a conventional approach fails. This index may constitute a promising tool for detection of postural troubles.