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Title
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An assessment of the information lost when applying data reduction techniques to dynamic plantar pressure measurements
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Author
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Abstract
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| Data reduction techniques are commonly applied to dynamic plantar pressure measurements, often prior to the measurements analysis. In performing these data reductions, information is discarded from the measurement before it can be evaluated, leading to unkonwn consequences. In this study, we aim to provide the first assessment of what impact data reduction techniques have on plantar pressure measurements. Specifically, we quantify the extent to which information of any kind is discarded when performing common data reductions. Plantar pressure measurements were collected from 33 healthy controls, 8 Hallux Valgus patients, and 10 Metatarsalgia patients. Eleven common data reductions were then applied to the measurements, and the resulting datasets were compared to the original measurement in three ways. First, information theory was used to estimate the information content present in the original and reduced datasets. Second, principal component analysis was used to estimate the number of intrinsic dimensions present. Finally, a permutational multivariate ANOVA was performed to evaluate the significance of group differences between the healthy controls, Hallux Valgus, and Metatarsalgia groups. The evaluated data reductions showed a minimum of 99.1% loss in information content and losses of dimensionality between 20.8% and 83.3%. Significant group differences were also lost after each of the 11 data reductions (), but these results may differ for other patient groups (especially those with highly-deformed footprints) or other region of interest definitions. Nevertheless, the existence of these results suggest that the diagnostic content of dynamic plantar pressure measurements is yet to be fully exploited. |
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Language
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English
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Source (journal)
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Journal of biomechanics. - New York, N.Y., 1968, currens
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Publication
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New York, N.Y.
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2019
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ISSN
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0021-9290
[print]
1873-2380
[online]
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DOI
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10.1016/J.JBIOMECH.2019.02.008
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Volume/pages
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87
(2019)
, p. 161-166
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ISI
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000465051200020
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Pubmed ID
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30824236
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Full text (Publisher's DOI)
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Full text (open access)
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