Identification of distinct characteristics of postural sway in Parkinson's disease: a feature selection procedure based on principal component analysis

Abstract

We selected descriptive measures of the centre of pressure (CoP) displacement in quiet standing, by means of a procedure based on principal component analysis, in two groups particularly different in terms of postural behaviours, such as subjects with Parkinson's disease (PD) in the levodopa off and on states. We computed 14 measures of the CoP: 5 measures of CoP trajectory over the support surface, 3 measures that estimated the area covered by the CoP, 1 measure that estimated the principal CoP sway direction, 1 measure that quantified the CoP total power, 1 measure that estimated the variability of CoP frequency content and 3 measures of characteristic CoP frequencies [L. Rocchi, L. Chiari, A. Cappello, Feature selection of stabilometric parameters based on principal component analysis, Med. Biol. Eng. Comput. 42 (2004) 71-79; L. Rocchi, L. Chiari, F.B. Horak, Effects of deep brain stimulation and levodopa on postural sway in Parkinson's disease, J. Neurol. Neurosurg. Psychiatry, 73 (2002) 267-274]. The feature selection, independently applied to the measures obtained in the two groups, resulted in different principal component (PC) subspaces of the 14-dimension original data set (4 PCs in the off and 3 PCs in the on state to account for over 90% of the original variance), but in the same 5 CoP measures (selected features) needed to describe the different postural behaviours: root mean square distance; mean velocity; principal sway direction; centroidal frequency of the power spectrum; frequency dispersion. The five selected features were found to provide insight into the postural control mechanisms and to describe changes in postural strategies in the two groups of PD subjects, off and on levodopa. Thus, the five selected features may be recommended for use in clinical practice and in research, in the direction toward the definition of a standard protocol in quantitative posturography.