METHOD AND APPARATUS FOR DEEP LEARNING OF FOOT CONTACTS AND FORCES

An approach to design a neural network estimates ground contact forces in various areas under each foot from motion capture data at an input. At training time, the input motion capture data is supplemented with synchronized pressure insole data and this extra data is leveraged to optimize neural network weights. At run-time, the optimized network is fed with motion capture data to regress the ground contact forces and predict more accurate ground contact from these forces. The data-driven foot contacts prediction method is learned on a large motion capture database which outperforms traditional heuristic approaches.