Abstract

Various walking speeds may induce different responses on the plantar pressure patterns. Current methods used to analyze plantar pressure patterns are linear and ignore nonlinear features. The purpose of this study was to analyze the complexity of plantar pressure images after walking at various speeds using nonlinear bidimensional multiscale entropy. Twelve participants were recruited for walking at three speeds for 20 minutes. A plantar pressure measurement system was used to measure plantar pressure patterns. Complexity index, a summation of MSE2D from all time scales, was used to quantify the changes of complexity of plantar pressure images. The analysis of variance with repeated measures and Fisher’s least significant difference correction were used to examine the results of this study. The results showed that CI of plantar pressure images of 1.8 mph was significantly lower compared with 3.6 and 5.4 mph. The results also showed that CI significantly increased from the 1st min to the 10th min and 20th min with slow walking. Our results indicate that slow walking at 1.8 mph may not be good for postural control compared with moderate walking and fast walking. This study demonstrates that bidimensional multiscale entropy is able to quantify complexity changes of plantar pressure images after different walking speeds.