Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 649743, 8 pages
Research Article

Principal Component Analysis of Gait Kinematics Data in Acute and Chronic Stroke Patients

1Faculty of Electrical Engineering, University of Belgrade, 11120 Belgrade, Serbia
2Tecnalia Serbia D.O.O., 11000 Belgrade, Serbia
3Center for Sensory Motor Interaction (SMI), Aalborg University, 9220 Aalborg, Denmark

Received 22 September 2011; Revised 9 November 2011; Accepted 14 November 2011

Academic Editor: Edelmira Valero

Copyright © 2012 Ivana Milovanović and Dejan B. Popović. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We present the joint angles analysis by means of the principal component analysis (PCA). The data from twenty-seven acute and chronic hemiplegic patients were used and compared with data from five healthy subjects. The data were collected during walking along a 10-meter long path. The PCA was applied on a data set consisting of hip, knee, and ankle joint angles of the paretic and the nonparetic leg. The results point to significant differences in joint synergies between the acute and chronic hemiplegic patients that are not revealed when applying typical methods for gait assessment (clinical scores, gait speed, and gait symmetry). The results suggest that the PCA allows classification of the origin for the deficit in the gait when compared to healthy subjects; hence, the most appropriate treatment can be applied in the rehabilitation.