Myoelectric control of a virtual hand based on third-order cumulants

This work presents a myoelectric control scheme of a virtual hand based on higher order statistics. The main objective of the experiments is to benefit the general amputee population, offering a training tool to potential prosthesis users. A simple and direct input control is based on the residual SEMG signals from the upper limb of amputee people. The third-order cumulant features are calculated recursively and a non-threshold control scheme is implemented online in a virtual hand. These SEMG features open and close the virtual hand assisted by the corresponding user's visual feedback. Seven experiments were concluded satisfactorily by an amputee volunteer.