Adaptive parameter selection for asynchronous intrafascicular multi-electrode stimulation

Abstract

This paper describes an adaptive algorithm for selecting perelectrode stimulus intensities and inter-electrode stimulation phasing to achieve desired isometric plantar-flexion forces via asynchronous, intrafascicular multi-electrode stimulation. The algorithm employed a linear model of force production and a gradient descent approach for updating the parameters of the model. The adaptively selected model stimulation parameters were validated in experiments in which stimulation was delivered via a Utah Slanted Electrode Array that was acutely implanted in the sciatic nerve of an anesthetized feline. In simulations and experiments, desired steps in force were evoked, and exhibited short time-to-peak (<; 0.5 s), low overshoot (<; 10%), low steady-state error (<; 4%), and low steady-state ripple (<; 12%), with rapid convergence of stimulation parameters. For periodic desired forces, the algorithm was able to quickly converge and experimental trials showed low amplitude error (mean error <; 10% of maximum force), and short time delay (<; 250 ms).