CareLit · DOI-Nachweis · Klinische Neurophysiologie
Significance of Principal Component Analysis (PCA) in characterization of gait pattern in parkinsonian patients
DOI 10.1055/s-0030-1250977
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Autor:innenC Holzhoffer, J Bürmann, Y Johann, S Bechtel, AK Louis, T Heider, K Fassbender, U Dillmann
ZeitschriftKlinische Neurophysiologie
Ausgabe03/2010
Jahrgang / SeitenNicht angegeben
Kernaussage aus der Literatur
Abstract-Vorschau
Introduction: PCA of parameters of gait pattern is a mathematic tool to reduce the redundant information from these parameters. In addition it is a powerful instrument to identify pathological gait pattern. Aim of our study was to analyse the significance of PCA in parkinsonian gait. Material and Methods: We analysed gait pattern during walking on a tread mill in 21 parkinsonian patients and 16 healthy controls usin…
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Zitierempfehlung
C Holzhoffer, J Bürmann, Y Johann, S Bechtel, AK Louis, T Heider, K Fassbender, U Dillmann (2010) Significance of Principal Component Analysis (PCA) in characterization of gait pattern in parkinsonian patients. Klinische Neurophysiologie (03). https://doi.org/10.1055/s-0030-1250977
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