Electrode array-based electrical stimulation using ILC with restricted input subspace

摘要: Electrode arrays are gaining increasing popularity within the rehabilitation and assistive technology communities, due to their potential deliver selective electrical stimulation underlying muscles. This paper develops first model-based control strategy in this area, unlocking for faster, more accurate postural control. Due time-varying nonlinear musculoskeletal dynamics, approach fuses model identification with iterative learning (ILC), employs a restricted input subspace comprising only those inputs deemed critical task completion. The selection embeds past experience and/or structural knowledge, dimension chosen affect trade-off between test time overall accuracy. Experimental results using 40 element surface electrode array confirm tracking of three reference hand postures.