Approximate entropy on posturographic data of diabetic subjects with peripheral neuropathy.

Posturographic time series (stabilogram) analysis is characterized by the difficulty to show the nature (deterministic or stochastic) of this signal. However, recent studies have shown a nonlinear chaotic behaviour of the stabilogram . Because of the intrinsic complexity of the stabilogram, the aim of this work is to analyze posturographic data without anyconsideration on their dynamics and to investigate their behaviour in terms of regularity and complexity. These latter characteristics can be useful to find differences, due to pathological conditions, in the signals dynamics. The variations of regularity and complexity in physiological signals can be revealed by Approximate Entropy (ApEn) . In this work ApEn has been evaluated for stabilograms related to diabetic subjects with Peripheral Neuropathy and to diabetic control subjects.