Reproduce “Towards AI-controlled FES-restoration of arm movements: neuromechanics-based reinforcement learning for 3-D reaching” on OpenResearch
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About this paper
Nat Wannawas, A.Aldo Faisal
The authors develop a reinforcement learning controller for functional electrical stimulation (FES) in simulated planar and three-dimensional arm models. It maps joint states and target angles to stimulation. After 300 training episodes, whole-trajectory joint-angle RMSEs are about 7° and 10°, and all reaches stay within a 5-centimeter endpoint target. These results demonstrate simulation feasibility, not performance in people.
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