tailieunhanh - Gait Pattern Classification of Healthy Elderly Men Based on Biomechanical Data

There were a total of three rounds in the task: the first two were hypothetical and the last was the actual round. A pen and a picture frame were used in the hypothetical situations, and a coffee mug was used for the actual situation. Only the actual round had a real payoff, either the mug or the cash value of the fixed offer. On the third round when each subject has determined their offer they wrote it on an index card and place it inside an envelope (both items were provided) along with the amount of the WTA or WTP | 579 Gait Pattern Classification of Healthy Elderly Men Based on Biomechanical Data Eric Watelain PhD Franck Barbier PhD Paul Allard PhD PEng André Thevenon MD Jean-Claude Angué PhD ABSTRACT. Watelain E Barbier F Allard p Thevenon A Angué J-C. Gait pattern classification of healthy elderly men based on biomechanical data. Arch Phys Med Rehabil 2000 81 579-86. Objectives To distinguish the gait patterns of young subjects from those of elderly men using three-dimensional 3D gait data to determine if elderly subjects displayed other than a typical gait pattern and to identify which parameters best describe them. Design Nonrandomized study in which video and force plate data were collected at the subject s own free walking speed and used in a 3D inverse dynamic model. Cluster analysis was chosen to identify the gait families and analyses of variance were performed to determine which parameters were different. Setting A gait laboratory. Participants The sample of convenience involved a single but mixed group consisting of 16 able-bodied elderly subjects mean age 62yrs and 16 able-bodied young subjects aged between 20 and 35 years. Main Outcome Measures Phasic and temporal gait parameters as well as the 3D muscle powers developed in the joints of the right lower limb during the gait cycle. Results The walking patterns in elderly subjects were found to be different from those of the young adults. Three elderly gait families or groups forming a specific gait pattern were identified and differences were found in the phasic and temporal parameters as well as in 6 peak muscle powers. Four of the peak powers occurred in the sagittal plane and half of them were related to the hip. Conclusions Biomechanical parameters can be used to classify the gait patterns of young and elderly men using cluster analysis rather than age alone. The muscle powers in elderly subjects are perturbed throughout the gait cycle and not only at push-off. It appears that the plane in which the peak .

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