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Effect of gap-filling technique and gap location on linear and nonlinear calculations of motion during locomotor activities
Marker occlusion during camera-based movement analysis is common. Different interpolation techniques are available for estimating location of missing marker trajectories. What is the effect of gap location and interpolation technique on linear and nonlinear measures for a given kinematic time series...
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Published in: | Gait & posture 2022-05, Vol.94, p.85-92 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Marker occlusion during camera-based movement analysis is common. Different interpolation techniques are available for estimating location of missing marker trajectories.
What is the effect of gap location and interpolation technique on linear and nonlinear measures for a given kinematic time series?
Kinematic data were recorded during motor-assisted elliptical training and treadmill walking. Gap-filling techniques (i.e., Cubic, Makima, Autoregressive, Nearest Neighbor, and No Interpolation) and gap locations experimentally applied to each cycle across initially complete time series (Gap 1: local minimum and maximum peaks; Gap 2: maximum peaks; Gap 3: maximum peaks at negative slope; Gap 4: random locations) were examined during linear (Maxima and Minima joint angles) and nonlinear [maximum Lyapunov exponent (LyE)] measures.
Gap-filling technique and gap location influenced values calculated for linear and nonlinear measures of joint motions. When referenced to the gold standard (original data series without gaps), across all joints studied the average % error of Maxima and Minima joint angles and LyE % error were lower when applying Cubic, Makima, Autoregressive, and Nearest Neighbor techniques compared to No Interpolation (p |
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ISSN: | 0966-6362 1879-2219 |
DOI: | 10.1016/j.gaitpost.2022.02.025 |