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Reduction of gait data variability using curve registration
Authors:Sadeghi H  Allard P  Shafie K  Mathieu P A  Sadeghi S  Prince F  Ramsay J
Institution:

a Human Movement Laboratory, Research Center, Sainte-Justine Hospital, 3175 Côte Ste-Catherine, Montreal, PQ, Canada H3T 1CS

b Department of Kinesiology, Tarbiat Moallem University, Ministry of Sciences, Research and Technology, Tehran, I.R., Iran

c Department of Kinesiology, University of Montreal, Montreal, PQ, Canada

d Department of Mathematics and Statistics, Shaid Beheshti University, Tehran I.R., Iran

e Department of Physiology and Biomedical Engineering Institute, University of Montreal, Montreal, PQ, Canada

f Department of Electrical and Computer Engineering, Concordia University, 1455 de Maisonneuve Blvd., West Montreal PQ, Canada

g Department of Psychology, McGill University, Montreal, PQ, Canada

Abstract:Timing in peak gait values shifts slightly between gait trials. When averaged, the standard deviation (S.D.) in gait data may increase due to this inter-trial variability unless normalization is carried out beforehand. The objective of this study was to determine how curve registration, an alignment technique, can reduce inter-subject variability in gait data without perturbing the curve characteristics. Twenty young, healthy men participated in this study each providing a single gait trial. Gait was assessed by means of a four-camera high-speed video system synchronized to a force plate. A rigid body three-segment model was used in an inverse dynamic approach to calculate three-dimensional muscle powers at the hip, knee and ankle. Curve registration was applied to each of the 20 gait trials to align the peak powers. The mean registered peak powers increased by an average of 0.10±0.13 W/kg with the highest increases in the sagittal plane at push-off. After performing curve registration, the RMS values decreased by 13.6% and the greatest reduction occurred at the hip and knee, both in the sagittal plane. No important discontinuities were reported in the first and second derivatives of the unregistered and registered curves. Curve registration did not have much effect on the harmonic content. This would be an appropriate technique for application prior to any statistical analysis using able-bodied gait patterns.
Keywords:Biomechanics  Gait pattern analysis  Continuous data  Curve registration technique
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