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TitleObjective graphical clustering of spatiotemporal gait pattern in patients with Parkinsonism
Author(s)Ferreira, Flora José Rocha
Gago, Miguel
Mollaei, Nafiseh
Bicho, Estela
Sousa, Nuno
Gama, João
Ferreira, Carlos
Gait analysis
Issue date2020
PublisherAssociação Internacional de Paremiologia (AIP-IAP)
JournalAIP Conference Proceedings
CitationFerreira, F., Gago, M., Mollaei, N., Bicho, E., Sousa, N., Gama, J., & Ferreira, C. (2020, November). Objective graphical clustering of spatiotemporal gait pattern in patients with Parkinsonism. In AIP Conference Proceedings (Vol. 2293, No. 1, p. 420101). AIP Publishing LLC
Abstract(s)The goal of this study was grouping patients with parkinsonism that share similar gait characteristics based on principal component analysis (PCA). Spatiotemporal gait data during self-selected walking were obtained from 15 patients with Vascular Parkinsonism, 15 patients with Idiopathic Parkinson's Disease and 15 Controls. PCA was used to reduce the dimensionality of 12 gait characteristics for the 45 subjects. Fuzzy C-mean cluster analysis was performed plotting the first two principal components, which accounted for 84.1% of the total variability. Results indicates that it is possible to quantitatively differentiate different gait types in patients with parkinsonism using PCA. Objective graphical classification of gait patterns could assist in clinical evaluation as well as aid treatment planning.
TypeConference paper
Publisher version
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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