title: Principal Component Analysis of gait in Parkinson's disease: relevance of gait velocity.
abstract: Principal Component Analysis (PCA) is a method to estimate the relation between data points. We used PCA to analyse movements of the upper and lower extremities during treadmill walking in healthy subjects and two groups of Parkinsonian patients. Healthy subjects (n=35) showed a typical pattern with high values of PC1 and low values in a descending order of PC2-PC4. Increase of speed resulted in a significant increase of PC1 and a significant decrease of the following PC's. In more severely affected patients (n=19, UPDRS>20), PC1 was significantly decreased and PC2-PC4 were significantly increased compared to healthy subjects. Speed could be increased only within a small range without corresponding changes of the PC's. In less severely affected patients (n=17), significant differences of the PC's were only found with fast pace. Separate analysis of arms and legs revealed that these changes are only due to altered movements of the arm. Analysis of the pattern of PC's in response to changes of gait velocities reveal alterations even in less severely affected Parkinsonian patients. The changes of the PC's with higher gait velocities in healthy subjects are suggestive of an increase of intersegmental coordination. This is impaired even in less severely affected Parkinsonian patients.
authors.affiliation: Department of Neurology, Saarland University Hospital, D-66421 Homburg, Saar, Germany. Electronic address: Ulrich.Dillmann@uks.eu.
authors.forename: Ulrich
authors.initials: U
authors.lastname: Dillmann
authors.affiliation: Department of Neurology, Saarland University Hospital, D-66421 Homburg, Saar, Germany.
authors.forename: Claudia
authors.initials: C
authors.lastname: Holzhoffer
authors.affiliation: Institute of Applied Mathematics, Department of Mathematics, Saarland University, D-66041 Saarbrücken, Germany.
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Johann
authors.affiliation: Institute of Applied Mathematics, Department of Mathematics, Saarland University, D-66041 Saarbrücken, Germany.
authors.forename: Sabrina
authors.initials: S
authors.lastname: Bechtel
authors.affiliation: Institute of Medical Biometrics, Epidemiology and Medical Informatics, Saarland University Hospital, D-66421 Homburg, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Gräber
authors.affiliation: Department of Neurology, Saarland University Hospital, D-66421 Homburg, Saar, Germany.
authors.forename: Christoph
authors.initials: C
authors.lastname: Massing
authors.affiliation: Department of Neurology, Saarland University Hospital, D-66421 Homburg, Saar, Germany.
authors.forename: Jörg
authors.initials: J
authors.lastname: Spiegel
authors.affiliation: Department of Neurology, Saarland University Hospital, D-66421 Homburg, Saar, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Behnke
authors.affiliation: Department of Neurology, Saarland University Hospital, D-66421 Homburg, Saar, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Bürmann
authors.affiliation: Institute of Applied Mathematics, Department of Mathematics, Saarland University, D-66041 Saarbrücken, Germany.
authors.forename: Alfred K
authors.initials: AK
authors.lastname: Louis
mesh_terms: D000054:Acceleration; D000328:Adult; D000368:Aged; D001696:Biomechanical Phenomena / Q000502:physiology; D016022:Case-Control Studies; D005080:Exercise Test; D005260:Female; D020233:Gait Disorders, Neurologic / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000503:physiopathology*; D025341:Principal Component Analysis; D012107:Research Design; D016138:Walking / Q000502:physiology
keywords: Gait analysis; Gait velocity; Parkinson's disease; Principal Component Analysis; UPDRS