In a significant proportion of individuals, the expected increase of body sway upon eye closure is not actually observed. This result prefigures different visual contributions to the fine regulation of body sway. The present paper documents a method to classify healthy subjects into one visual or non-visual group according to the fractal properties of center of pressure (COP) profiles. The recognition of the sensory strategy consists of several phases: first, stabilogram diffusion analysis is carried out on the time-series of COP; then, stochastic features are extracted by two models of different complexity. In particular, a new technique is proposed which describes with continuity the transition among different scaling regimes. Finally, a linear classifier is designed. The method gave very high performance classifying, with the best set of features, provided by the two parameters of the new model, 93.3% of the examined subjects in agreement with the preclassification, provided by percentage difference of sway between eyes open and eyes closed conditions and computed over the area of the 95% confidence ellipse. © 2000 Elsevier Science B.V.

Chiari L., Bertani A., Cappello A. (2000). Classification of visual strategies in human postural control by stochastic parameters. HUMAN MOVEMENT SCIENCE, 19(6), 817-842 [10.1016/S0167-9457(01)00024-0].

Classification of visual strategies in human postural control by stochastic parameters

Chiari L.
;
Bertani A.;Cappello A.
2000

Abstract

In a significant proportion of individuals, the expected increase of body sway upon eye closure is not actually observed. This result prefigures different visual contributions to the fine regulation of body sway. The present paper documents a method to classify healthy subjects into one visual or non-visual group according to the fractal properties of center of pressure (COP) profiles. The recognition of the sensory strategy consists of several phases: first, stabilogram diffusion analysis is carried out on the time-series of COP; then, stochastic features are extracted by two models of different complexity. In particular, a new technique is proposed which describes with continuity the transition among different scaling regimes. Finally, a linear classifier is designed. The method gave very high performance classifying, with the best set of features, provided by the two parameters of the new model, 93.3% of the examined subjects in agreement with the preclassification, provided by percentage difference of sway between eyes open and eyes closed conditions and computed over the area of the 95% confidence ellipse. © 2000 Elsevier Science B.V.
2000
Chiari L., Bertani A., Cappello A. (2000). Classification of visual strategies in human postural control by stochastic parameters. HUMAN MOVEMENT SCIENCE, 19(6), 817-842 [10.1016/S0167-9457(01)00024-0].
Chiari L.; Bertani A.; Cappello A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/875101
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