Artificial Neural Networks and Center-of-Pressure Modeling: A Practical Method for Sensorimotor-Degradation Assessment

in Journal of Aging and Physical Activity
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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.

Shan and Daniels are with the Dept. of Kinesiology, University of Lethbridge, Alberta, Canada T1K 3M4. Gu is with the Dept. of Exercise Physiology, Shandong Sport Science Institute, Jinan, Shandong, 250014 China.

Journal of Aging and Physical Activity
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