Designing a cross-trainerusing an artificial neural network

Cross-trainers are machines that use link mechanisms to mimic walking or running aspart of workout sessions or rehabilitation systems. The simplest cross-trainer incorporatesa crank-rocker or a crank-slider mechanism and provides a nearly elliptical path for footmotion. However, the natural human foot trajectories are far from being elliptical. Therefore, existing designs require modifications. Artificial neural networks are used for thispurpose. Instead of trying to match the foot trajectory directly, here we tried to matchdifferent geometric properties of the area enclosed by the foot trajectory. Neural networksare trained to predict these geometric properties as outputs with the dimensions of thelinkage as inputs. With the help of the same trained network, the “best-fit dimensions”were predicted for the desired trajectories.

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Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).