The Expanded Disability Status Scale (EDSS) is the most widely used scale to evaluate the degree of neurological impairment in multiple sclerosis (MS). In this paper, we report on the evaluation of an EDSS modeling strategy based on recurrence quantification analysis (RQA) of posturographic data (i.e., center of pressure, COP). A total of 133 volunteers with EDSS ranging from 0 to 4.5 participated in this study, with eyes closed. After selection of time delay (τ), embedding dimension (m) as well as threshold (radius, r) to identify recurrent points, several RQA measures were calculated for each COP's position and velocity data in the mono- and multi-dimensional RQAs. Estimation results lead to the selection of the recurrence rate (RR) of the COP's position as the most pertinent RQA measure. The performance of the models versus raw and noisy data was higher in the mono-dimensional analysis than in the multi-dimensional. This study suggests that the posturographic signal's mono-dimensional RQA is a more pertinent method to quantify disability in MS than the multi-dimensional RQA.
Keywords: Center of pressure (COP); Expanded Disability Status Scale (EDSS); Mono- and multi-dimensional analyses; Multiple sclerosis (MS); Posturographic data; Recurrence quantification analysis (RQA).