Complex systems have some constitutive properties that ensure the robustness and flexibility required for adaptability and sustainability. It was suggested that if young and healthy subjects are characterized by a high level of complexity, aging, however, is marked by a significant alteration of complexity.
One can assess the level of complexity of these systems, by analyzing the fluctuations yielded in times series of motor performances. These fluctuations present a typical structure, characterized by a phenomenon called long-range correlations (LRC). Under natural tasks (low constraints), the presence of such correlations is the signature of these complex systems. Conversely, the alteration of these correlations can be expressed either by a lack of coordination in the system (low correlations in signals) or by a too rigid coordination (increased correlations) and indicates a loss of complexity.
For example, Hausdorff et al. (1997) showed that elderly subject presents a lower correlational structure in stride intervals, compared to young subjects. Furthermore, the results show that the alteration of long-term correlations, thus the loss of complexity, correlates with the propensity to fall.
The main objective of this thesis is to test the predictive power of complex measures, in order to provide early tests of frailty. We assume that an alteration of complexity might reveal, before classical clinical tests, the early signs of accelerated aging.
We determined a battery of tests that will allow us a multivariate measure of complexity. These tests will be offered to a cohort of subjects from the Centre Régional Equilibre et Prévention des Chutes.