Center of mass approximation and prediction as a function of body acceleration.

In order to maintain postural stability, the central nervous system must maintain equilibrium of the total center of body mass (COM) in relation to its base of support. Thus, the trajectory of the COM provides an important measure of postural stability. Three different models were developed to estimate the COM and the results tested on 16 subjects: namely a neural network, an adaptive fuzzy interface system and a hybrid genetic algorithm sum-of-sines model. The inputs to the models were acquired via two accelerometers, one representing the trunk segment placed on T2 and the second representing the limb segment placed on the shank below the knee joint. The portability, ease of use and low cost (compared with video motion analysis systems) of the accelerometers increases the range of clinics to which the system will be available. The subjects performed a multisegmental movement task on fixed and foam surfaces, thus covering a relatively wide dynamic scope. The results are encouraging for obtaining COM estimates that have clinical applications; the genetic sum-of-sines model was found to be superior when compared to the other two models.