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The center of foot pressure (COP) is a commonly used output measure of the postural control system as it is indicative of the systems stability. A dense piece of foam, i.e., a sponge, can be used to emulate random environmental conditions that distort the ground reaction forces received and interpreted by the cutaneous sensors in the feet; thus introducing uncertainty into the control system. In this paper, the density and size of the sponge was selected such that a subject's weight did not cause full compression. In general, the COP is measured from the bottom of the sponge. As the sponge is used to distort ground reaction forces, it is reasonable then to assume that the COP signal would also be distorted. The use of other sensory information to identify state of balance, and compute necessary balance adjustments, is therefore required. In addition to a sponge, many different types of specialized footwear and inserts are used for people with peripheral neuropathy, such as diabetics. However, it is difficult to design diabetic footwear without a better understanding of the mechanical and physiological effects that different surfaces typical of outdoor terrains, such as a sponge, which cannot be predicted without the sense of the foot, have on balance. Therefore, the goal of this study was to investigate the change of the COP signal from the top and bottom of the sponge. Portable force sensing mats from Vista Medical were used to obtain the COP from the top and bottom of the sponge. The COP measured on the bottom of the sponge is not the same as the COP measured on the top, particularly in the medial-lateral direction. Several linear and nonlinear models were used to identify the unknown plant; i.e., the sponge. Overall, the nonlinear neural network method had superior performance when compared with the linear models. Thus, the results indicate that the signals from the top and bottom of the sponge are in fact different, and furthermore, they are nonlinearly related- - . A nonlinear mathematical model is proposed which describes COP distortion through a medium such as a sponge. Although the values for the model parameters determined were for a particular sponge, this study suggests that a neural network plant identification model may be applied to any medium other than the sponge; the information can then be used to determine how the balance control model is affected given the sensory information received.