title: Application of principal component analysis in clinical gait research: identification of systematic differences between healthy and medial knee-osteoarthritic gait.
abstract: For a successful completion of a movement task the motor control system has to observe a multitude of internal constraints that govern the coordination of its segments. The purpose of this study was to apply principal component (PC) analysis to detect differences in the segmental coordination between healthy subjects and patients with medial knee osteoarthritis (OA). It was hypothesized that (1) systematic differences in patterns of whole body movement would be identifiable with this method even in small sample sized groups and that (2) these differences will include compensatory movements in the OA patients in both the lower and upper body segments. Marker positions and ground reaction forces of three gait trials of 5 healthy and 5 OA participants with full body marker sets were analyzed using a principal component analysis. Group differences in the PC-scores were determined for the first 10 PC-vectors and a linear combination of those PC-vectors where differences were found defined a discriminant vector. Projecting the original trials onto this discriminant vector yielded significant group differences (t(d=8)=3.011; p=0.017) with greater upper body movement in patients with knee OA that was correlated with the medial-lateral ground reaction force. These results help to characterize the adaptation of whole-body gait patterns to knee OA in a relatively small population and may provide an improved basis for the development of interventions to modify knee load. The PC-based motion analysis offered a highly sensitive approach to identify characteristic whole body patterns of movement associated with pathological gait.
authors.affiliation: Mechanical Engineering, Stanford University, Stanford, CA, USA. peter.federolf@nih.no
authors.forename: P A
authors.initials: PA
authors.lastname: Federolf
authors.forename: K A
authors.initials: KA
authors.lastname: Boyer
authors.forename: T P
authors.initials: TP
authors.lastname: Andriacchi
mesh_terms: D001696:Biomechanical Phenomena; D018592:Cross-Over Studies; D004311:Double-Blind Method; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D007719:Knee Joint / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000503:physiopathology*; D010388:Pelvis; D025341:Principal Component Analysis; D012782:Shoulder
keywords: Bernstein′s degree of freedom problem; Kinematics; Locomotion; Principal component analysis PCA; Small sample size