| ||Format||Pages||Price|| |
|PDF (356K)||16||$25||  ADD TO CART|
|Complete Source PDF (7.5M)||389||$109||  ADD TO CART|
The relationships between moments predicted at the frequent sites of injury during snow skiing and “high” and “low” electromyographic measures and weight bearing in the leg are used to develop a ski binding release algorithm that continuously controls the retention setting. The algorithm is based on concepts of fuzzy logic. Simulations of the performance of the algorithm, tested with data collected during 101 ski test runs in field experiments, revealed nine different actual release/retention actions than occurred with the conventional binding during the experiments. In five cases where the conventional binding released possibly prematurely, the simulated algorithm did not predict release. In two cases when the subject fell during moderate weight bearing and muscle contraction, the conventional binding did not release and the algorithm predicted twist release.
The algorithm demonstrates promise to address simultaneously some of the key problems of inadvertent and inadequate binding release. These results suggest that reduction of the number of inadvertent releases requires better prediction of the forces and moments at the sites of potential injury, and binding designs that reduce the retention threshold during intervals of low weight bearing and muscle contraction may also better control the forces and moments at the sites of potential injury.
fuzzy logic, adaptive control, skiing injury, ski binding
Graduate student, University of California, Berkeley, California
Vice chancellor, FANUC chair in mechanical systems, University of California, Berkeley, California