title: Selectivity of multiple-contact nerve cuff electrodes: a simulation analysis.
abstract: Advances in functional neuromuscular stimulation (FNS) have increased the need for nerve cuff designs that can control multiple motor functions through selective stimulation of selected populations of axons. This selectivity has proved to be difficult to achieve. Recent experiments suggest that it is possible to slowly reshape peripheral nerve without affecting its physiological function. Using computer simulations we have tested the hypothesis that changing the cross section of a nerve from a round to a flat configuration can significantly improve the selectivity of a nerve cuff. We introduce a new index to estimate selectivity to evaluate the various designs. This index is based on the ability of a nerve electrode to stimulate a target axon without stimulating any other axons. The calculations involve a three-dimensional finite element model to represent the electrical properties of the nerve and cuff and the determination of the firing properties of individual axons. The selectivity rating was found to be significantly higher for the Flat Cuff than the Round Cuff. The result was valid with uniform or random distribution of axons and with a random distribution of fascicles diameters. Flattening of individual fascicles also improved the selectivity of the Flat Cuff but only when the number of contacts used was increased to maintain uniform contact density. Therefore, cuff designs that can reshape the nerve into flatter configurations should yield better cuff performance than the cylindrical cuffs but will require higher contact density.
authors: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: A Q
authors: AQ
authors: Choi
authors: J K
authors: JK
authors: Cavanaugh
authors: D M
authors: DM
authors: Durand
mesh_terms: D016880:Anisotropy; D001369:Axons / Q000502:physiology; D004599:Electric Stimulation Therapy / Q000295:instrumentation*; D004566:Electrodes; D004867:Equipment Design; D008564:Membrane Potentials; D008959:Models, Neurological; D011999:Recruitment, Neurophysiological