Identifying nonlinear dynamics of CoP during upright standing using muscle activation pattem

Postural balance plays an important role in daily activities, optimal performance and injury prevention. Recent studies suggest that identifying nonlinear dynamics of center of pressure (CoP) can be useful in evaluating postural balance. Thus, the purpose of this study is to propose a model that estimates the CoP signal at any moment using ankle muscle activation pattern. Electromyogram signals of two muscles (Tibialis Anterior and Medial Gastrocnemius) and CoP of healthy subjects during upright standing were recorded simultaneously. In this research, a discrete nonlinear and linear time series models derived from an ARX (autoregressive with exogeneous input) model are proposed to determine the nonlinear dynamics of the CoP. The inputs and outputs of model are ankle muscle activation pattern and CoP, respectively. The root mean square error (RMSE), R-squared (R2), Pearson correlation coefficient (Pea) and variance accounted for (VAF) were used for model evaluation. Variance accounted for is above 99%. Moreover, the correlation coefficient and R-squared are more than 0.99 and the root mean square error is also very low. The results show that these proposed models have a good performance and can directly identify the pressure center dynamics.