首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Application of principal component analysis in clinical gait research: Identification of systematic differences between healthy and medial knee-osteoarthritic gait
Authors:PA Federolf  KA Boyer  TP Andriacchi
Institution:1. Mechanical Engineering, Stanford University, Stanford, CA, USA;2. Norwegian School of Sport Sciences, P.O. Box 4014 Ulleval Stadion, 0806 Oslo, Norway;3. Bone and Joint Center, VA Palo Alto Health Care System, Palo Alto, CA, USA;4. School of Medicine, Stanford University, Stanford, CA, USA;5. Department of Kinesiology, University of Massachusetts-Amherst, Amherst, MA, USA
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.
Keywords:Kinematics  Principal component analysis PCA  Locomotion  Bernstein&prime  s degree of freedom problem  Small sample size
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号