The study of stabilogram is an important step in postural control analysis. This paper presents an analysis of stabilogram using the mPCA decomposition and shows the effects of different aspects on the human postural stability. The aim of this study is to analyze stabilogram center of pressure time series using the mPCA (modified Principal Analysis Component) decomposition method. This method is suitable to be applied to a complex time series such as postural signal, using an additive model, to decompose the stabilogram into three components: trend, rambling and trembling. Studying the trace of analytic trembling (respectively of rambling) in the complex plan highlights a unique rotation center. This specification allows the definition of the phase and so the extraction of phase fluctuation. Adapting the stabilogram diffusion analysis method (SDA), Hurst exponents (H1 and H2) are extracted from the diffusion of phase's fluctuations related either to trembling and rambling. These parameters represent efficient informers of the postural equilibrium status of healthy subjects (average age 31 ± 11 years) . Experimental results show that for rambling and trembling the fluctuations of the phase, having a uniform rotation, can be described as to be fractional Brownian random processes. So, the fluctuations phase diffusion of trembling and rambling are identified by two regions; a short- term region and a long-term region. The extraction of H1 related to short-term region extracted by SDA technique show that the fluctuations phase of trembling present persistence (H1 > 1/2). Otherwise, fluctuations phase of rambling present an anti-persistence (H1 > 1/2). The results show also that direction, visual and proprioceptive entries haven't any effects on the Hurst exponents related to rambling and trembling fluctuations phase.
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