RESUMO

The purpose of this study was to investigate the effects of different vertical positions of an asymmetrical load on the anticipatory postural adjustments phase of gait initiation. Sixty-eight college students (32 males, 36 females; age: 23.65 ± 3.21 years old; weight: 69.98 ± 8.15 kg; height: 1.74 ± 0.08 m) were enrolled in the study. Ground reaction forces and moments were collected using two force platforms. The participants completed three trials under each of the following random conditions: no-load (NL), waist uniformly distributed load (WUD), shoulder uniformly distributed load (SUD), waist stance foot load (WST), shoulder stance foot load (SST), waist swing foot load (WSW), and shoulder swing foot load (SSW). The paired Hotelling's T-square test was used to compare the experimental conditions. The center of pressure (COP) time series were significantly different for the SUD vs. NL, SST vs. NL, WST vs. NL, and WSW vs. NL comparisons. Significant differences in COP time series were observed for all comparisons between waist vs. shoulder conditions. Overall, these differences were greater when the load was positioned at the shoulders. For the center of mass (COM) time series, significant differences were found for the WUD vs. NL and WSW vs. NL conditions. However, no differences were observed with the load positioned at the shoulders. In conclusion, only asymmetrical loading at the waist produced significant differences, and the higher the extra load, the greater the effects on COP behavior. By contrast, only minor changes were observed in COM behavior, suggesting that the changes in COP (the controller) behavior are adjustments to maintain the COM (controlled object) unaltered.

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RESUMO

Este estudo analisou a eficiência de diferentes algoritmos de máquina de vetor de suporte (SVM) para discriminar dados de diferentes sujeitos. Utilizou-se dados previamente coletados de idosos e jovens com 3 coletas por sujeito, em um estudo de controle postural na plataforma de força. Os dados foram analisados a partir da densidade espectral de potência (PSD) do centro de pressão sobre a qual foi aplicada a análise de componentes principais (PCA) para reduzir a dimensionalidade dos dados. A SVM recebeu a PCA com 90% de variância da PSD original e utilizando diferentes núcleos de produto interno calculou a eficiência de cada um para diferenciar grupos com características distintas.A SVM que obteve o melhor desempenho foi a de núcleo Polinomial, com uma eficiência de 90% aproximadamente, no entanto, o resultado é dependente dos dados a serem classificados, e se faz necessário então uma ferramenta que possa utilizar diferentes núcleos.

This study analyze the efficiency of different algorithms of support vector machine (SVM) to discriminate data from different subjects. It was used data previously collected from elderly and young people with 3 collectionsby subject, in a postural control study on a force plate. Data were analyzed from the power spectral density (PSD)of the center of pressure on which was applied principal component analysis (PCA) to reduce the dimensionality ofthe data. The SVM received the PCA with 90% of the variance of the original PSD and using different inner productkernels was calculated the efficiency of each one to differentiate between groups with different characteristics. TheSVM that have the best performances was the Polynomial with an efficiency of 90% approximately, however, the result depends on data to be classified and it is necessary then a tool that can use different cores.

Assuntos