A novel approach to study human posture control: “Principal movements” obtained from a principal component analysis of kinematic marker data

Human upright posture is maintained by postural movements, which can be quantified by “principal movements” (PMs) obtained through a principal component analysis (PCA) of kinematic marker data. The current study expands the concept of “principal movements” in analogy to Newton׳s mechanics by definin...

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Veröffentlicht in:Journal of biomechanics Jg. 49; H. 3; S. 364 - 370
1. Verfasser: Federolf, Peter A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Elsevier Ltd 08.02.2016
Elsevier Limited
Schlagworte:
Adult
Ankle
Balance
Biomechanical Phenomena
Center of pressure COP
Female
Human
Human movement
Humans
Kinematics
Male
Markers
Mathematical analysis
Motor control
Movement
Movements
PAS
Physical Medicine and Rehabilitation
Postural Balance
Posture
Principal Component Analysis
Principal component analysis PCA
Principal movements
Regression Analysis
Sensitivity and Specificity
Sports injuries
Stability
Variance
Young Adult
Center of pressure COP
Stability
Principal component analysis PCA
Principal movements
Motor control
Balance
Human movement
ISSN:0021-9290, 1873-2380
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Zusammenfassung:Human upright posture is maintained by postural movements, which can be quantified by “principal movements” (PMs) obtained through a principal component analysis (PCA) of kinematic marker data. The current study expands the concept of “principal movements” in analogy to Newton׳s mechanics by defining “principal position” (PP), “principal velocity” (PV), and “principal acceleration” (PA) and demonstrates that a linear combination of PPs and PAs determines the center of pressure (COP) variance in upright standing. Twenty-one subjects equipped with 27-markers distributed over all body segments stood on a force plate while their postural movements were recorded using a standard motion tracking system. A PCA calculated on normalized and weighted posture vectors yielded the PPs and their time derivatives, the PVs and PAs. COP variance explained by the PPs and PAs was obtained through a regression analysis. The first 15 PMs quantified 99.3% of the postural variance and explained 99.60%±0.22% (mean±SD) of the anterior–posterior and 98.82±0.74% of the lateral COP variance in the 21 subjects. Calculation of the PMs thus provides a data-driven definition of variables that simultaneously quantify the state of the postural system (PPs and PVs) and the activity of the neuro-muscular controller (PAs). Since the definition of PPs and PAs is consistent with Newton׳s mechanics, these variables facilitate studying how mechanical variables, such as the COP motion, are governed by the postural control system.
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ISSN:0021-9290
1873-2380
DOI:10.1016/j.jbiomech.2015.12.030