The aim of this work is to determine whether postural sway can be well described by nonlinear deterministic modelling. Since the results of nonlinear analysis depend on experimental data processing, emphasis was given to the assessment of a proper methodology to process posturographic data. Centre of Pressure (CoP) anteriorposterior (AP) displacements (stabilogram) were obtained by static posturography tests performed on control subjects. A nonlinear determinism test was applied to investigate the nature of data. A nonlinear filtering method allowed us to estimate properly the parameters of the nonlinear model without altering signal dynamics. The largest Lyapunov exponent (LLE) was estimated to quantify the chaotic behaviour of postural sway. LLE values were found to be positive although close to zero. This suggests that postural sway derives from a process exhibiting weakly chaotic dynamics.

Nonlinear analysis of posturographic data / L., Ladislao; Fioretti, Sandro. - In: MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING. - ISSN 0140-0118. - 45:(2007), pp. 679-688.

Nonlinear analysis of posturographic data.

FIORETTI, Sandro
2007-01-01

Abstract

The aim of this work is to determine whether postural sway can be well described by nonlinear deterministic modelling. Since the results of nonlinear analysis depend on experimental data processing, emphasis was given to the assessment of a proper methodology to process posturographic data. Centre of Pressure (CoP) anteriorposterior (AP) displacements (stabilogram) were obtained by static posturography tests performed on control subjects. A nonlinear determinism test was applied to investigate the nature of data. A nonlinear filtering method allowed us to estimate properly the parameters of the nonlinear model without altering signal dynamics. The largest Lyapunov exponent (LLE) was estimated to quantify the chaotic behaviour of postural sway. LLE values were found to be positive although close to zero. This suggests that postural sway derives from a process exhibiting weakly chaotic dynamics.
2007
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/31808
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