Test-retest reliability of multiscale fractal dimension measurements of plantar pressure maps during dynamic tasks

Carrasco, Aline Cristina; Silva, Mariana F.; Guenka, Leandro Caetano; Bueno, Murilo J.O.; Bela, Laís Faganello Dela; Torres, Ricardo da S.; Moura, Felipe Arruda; Cardoso, Jefferson Rosa

doi:10.1016/j.jbiomech.2020.110103

Cited by 1 publication

(1 citation statement)

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“…This was a cross-sectional study, which was conducted in the biomechanical laboratory in accordance with the guidelines for research on reporting reliability and consistency (GRRAS). 27,29 All methods were approved by the IRB and subjects completed informed consent forms.…”

Section: Methodsmentioning

confidence: 99%

Study on foot-type classification for young adults based on static and dynamic plantar pressure distribution

Tang

Wang

et al. 2022

Advances in Mechanical Engineering

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The application of an effective and reliable foot type classification method is very important for foot type judgment, injury risk assessment, and correction. Therefore, this paper mainly aims to propose a new foot type classification method for young people based on bitmap index (BI), compare it with the traditional footprint classification method, and put forward and analyze the factors affecting foot type classification. Thirty-one healthy volunteers were asked to perform two types tests in order to study the plantar pressure distribution with static and dynamic conditions, the first type is footprint test with full load of static, and the other type is plantar pressure distribution, which contains four different tests: no load, half load, and full load of static state, as well as dynamic plantar pressure distribution during process of walking. The Intraclass Correlation Coefficient results (ICC) were good reliable and reproducible for BI value with dynamic test (DT-BI value 0.738, 95% confidence interval [0.535, 0.848], [Formula: see text]) and full-load (FL-BI value 0.725 [0.281, 0.814], [Formula: see text], p < 0.001), obtained with individual measures and a two-way mixed-effects model. It can be seen from Kappa coefficient and density map that DT-BI has high classification accuracy. Classification of foot type based on bitmap index values showed good reliability in people with varying BMI, which can help clinicians and researchers segment the sample population to better distinguish between different foot types of activity, gait or treatment effects.

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Section: Methodsmentioning

confidence: 99%