Arthur de Sá Ferreira1, Patrícia Junqueira Ferraz Baracat2. 1. Laboratory of Computational Simulation and Modeling in Rehabilitation, Postgraduate Program in Rehabilitation Science, Centro Universitário Augusto Motta/UNISUAM, Rio de Janeiro, RJ, Brazil. Electronic address: arthur_sf@ig.com.br. 2. Laboratory of Computational Simulation and Modeling in Rehabilitation, Postgraduate Program in Rehabilitation Science, Centro Universitário Augusto Motta/UNISUAM, Rio de Janeiro, RJ, Brazil.
Abstract
INTRODUCTION: This study investigated the test-retest reliability for assessment of postural stability using a quantitative method for identification of center of pressure (CoP) spatial patterns of three-dimensional statokinesigrams (3D-SKG). METHODS: Twenty-one healthy participants (11 women, age 26.8 ± 7.2 years, body mass index 25.6 ± 5.3 kg/m²) were submitted to four consecutive 60-s trials while performing undisturbed upright stance with feet together, with or without visual input each. CoP data was used to calculate parameters from the 3D-SKG (quantity of high-density regions, nHDR). Stabilogram (standard deviation, range, maximum velocity) and statokinesigram (elliptical area, average velocity) were also calculated. Intraclass correlation coefficients (ICC2,1 and ICC2,4) and repeated-measures analysis-of-variance were used for statistical analysis. RESULTS: Significant differences in nHDR among trials were not noticed in both protocols, as well as for any parameter of the stabilogram or statokinesigram (all P > 0.05). Reliability for identification of nHDR with or without visual input was either excellent (ICC2,4 = 0.844 and 0.792, respectively) or fair to good (ICC2,1 = 0.575 and 0.488, respectively). Reliability of parameters from stabilogram and statokinesigram varied from excellent to poor for either postural task with (ICC2,4 range: 0.961-0.491; ICC2,1 range: 0.859-0.194) or without visual input (ICC2,4 range: 0.990-0.444; ICC2,1 range: 0.960-0.166). CONCLUSIONS: Test-retest reliability for identification of CoP spatial patterns is excellent or fair to good using averaged or single measurements of nHDR, respectively. No learning effect on repeated trials for identification of CoP spatial patterns was detected but deserves further research.
INTRODUCTION: This study investigated the test-retest reliability for assessment of postural stability using a quantitative method for identification of center of pressure (CoP) spatial patterns of three-dimensional statokinesigrams (3D-SKG). METHODS: Twenty-one healthy participants (11 women, age 26.8 ± 7.2 years, body mass index 25.6 ± 5.3 kg/m²) were submitted to four consecutive 60-s trials while performing undisturbed upright stance with feet together, with or without visual input each. CoP data was used to calculate parameters from the 3D-SKG (quantity of high-density regions, nHDR). Stabilogram (standard deviation, range, maximum velocity) and statokinesigram (elliptical area, average velocity) were also calculated. Intraclass correlation coefficients (ICC2,1 and ICC2,4) and repeated-measures analysis-of-variance were used for statistical analysis. RESULTS: Significant differences in nHDR among trials were not noticed in both protocols, as well as for any parameter of the stabilogram or statokinesigram (all P > 0.05). Reliability for identification of nHDR with or without visual input was either excellent (ICC2,4 = 0.844 and 0.792, respectively) or fair to good (ICC2,1 = 0.575 and 0.488, respectively). Reliability of parameters from stabilogram and statokinesigram varied from excellent to poor for either postural task with (ICC2,4 range: 0.961-0.491; ICC2,1 range: 0.859-0.194) or without visual input (ICC2,4 range: 0.990-0.444; ICC2,1 range: 0.960-0.166). CONCLUSIONS: Test-retest reliability for identification of CoP spatial patterns is excellent or fair to good using averaged or single measurements of nHDR, respectively. No learning effect on repeated trials for identification of CoP spatial patterns was detected but deserves further research.
Authors: Emily J Werder; Dale P Sandler; David B Richardson; Michael E Emch; Richard K Kwok; Fredric E Gerr; Lawrence S Engel Journal: Environ Health Perspect Date: 2019-04 Impact factor: 9.031
Authors: Jussara A O Baggio; Suleimy S C Mazin; Frederico F Alessio-Alves; Camila G C Barros; Antonio A O Carneiro; João P Leite; Octavio M Pontes-Neto; Taiza E G Santos-Pontelli Journal: PLoS One Date: 2016-03-08 Impact factor: 3.240