Artificial neural networks and center-of-pressure modeling: a practical method for sensorimotor-degradation assessment.

Numerous methods for studying the prevention of falls and age-related sensorimotor degradation have been proposed and tested. Some approaches are too impractical to use with seniors or too expensive for practitioners. Practitioners desire a simple, reliable technique. The goals of this research were to develop such an approach and to apply it in exploring the effect of Tai Chi on age-related sensorimotor degradation. The method employed artificial-neural-network (ANN) models trained by using individuals' center-of-pressure (COP) measurements and age. Ninety-six White and Chinese adults without Tai Chi training were tested. In contrast, a third group, Chinese seniors with Tai Chi training, was tested to ascertain any influence from Tai Chi on sensorimotor aging. This study supported ANN technology with COP data as a feasible tool in the exploration of sensorimotor degradation and demonstrated that Tai Chi slowed down the effects of sensorimotor aging.

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