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

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...

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Detalles Bibliográficos
Autores: Nieto Reyes, Alicia|||0000-0002-0268-3322, Battey, Heather, Francisci, Giacomo
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/35234
Acceso en línea:https://hdl.handle.net/10902/35234
Access Level:acceso abierto
Palabra clave:Alzheimer’s disease
Dementia
Functional data analysis
Functional depth
Statistical data depth
Symmetry
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spelling Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patientsNieto Reyes, Alicia|||0000-0002-0268-3322Battey, HeatherFrancisci, GiacomoAlzheimer’s diseaseDementiaFunctional data analysisFunctional depthStatistical data depthSymmetryBlack-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.For A.N.-R., this research was funded by grant number MTM2017-86061-C2-2-P of the Spanish Ministry of Science, Innovation and Universities. H.B was supported by the EPSRC under grant number EP/P002757/1MDPIUniversidad de Cantabria20212021-04-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttps://hdl.handle.net/10902/35234Mathematics, 2021, 9(8), 820reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/352342026-06-02T12:39:31Z
dc.title.none.fl_str_mv Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
title Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
spellingShingle Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
Nieto Reyes, Alicia|||0000-0002-0268-3322
Alzheimer’s disease
Dementia
Functional data analysis
Functional depth
Statistical data depth
Symmetry
title_short Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
title_full Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
title_fullStr Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
title_full_unstemmed Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
title_sort Functional symmetry and statistical depth for the analysis of movement patterns in Alzheimer's patients
dc.creator.none.fl_str_mv Nieto Reyes, Alicia|||0000-0002-0268-3322
Battey, Heather
Francisci, Giacomo
author Nieto Reyes, Alicia|||0000-0002-0268-3322
author_facet Nieto Reyes, Alicia|||0000-0002-0268-3322
Battey, Heather
Francisci, Giacomo
author_role author
author2 Battey, Heather
Francisci, Giacomo
author2_role author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Alzheimer’s disease
Dementia
Functional data analysis
Functional depth
Statistical data depth
Symmetry
topic Alzheimer’s disease
Dementia
Functional data analysis
Functional depth
Statistical data depth
Symmetry
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-04-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10902/35234
url https://hdl.handle.net/10902/35234
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Mathematics, 2021, 9(8), 820
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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