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Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer?s patients

Abstract: Black-box techniques have been applied with outstanding results to classify, in a supervised manner, the movement patterns of Alzheimer?s patients according to their stage of the disease. However, these techniques do not provide information on the difference of the patterns among the stages. We make use of functional data analysis to provide insight on the nature of these differences. In particular, we calculate the center of symmetry of the underlying distribution at each stage and use it to compute the functional depth of the movements of each patient. This results in an ordering of the data to which we apply nonparametric permutation tests to check on the differences in the distribution, median and deviance from the median. We consistently obtain that the movement pattern at each stage is significantly different to that of the prior and posterior stage in terms of the deviance from the median applied to the depth. The approach is validated by simulation.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Mathematics, 2021, 9, 820

Editorial: MDPI

 Fecha de publicación: 01/04/2021

Nº de páginas: 17

Tipo de publicación: Artículo de Revista

 DOI: 10.3390/math9080820

ISSN: 2227-7390

Proyecto español: MTM2017-86061-C2-2-P