A model of selective activation of the femoral nerve with a flat interface nerve electrode for a lower extremity neuroprosthesis.

Functional electrical stimulation (FES) can restore limb movements through electrically initiated, coordinated contractions of paralyzed muscles. The peripheral nerve is an attractive site for stimulation using cuff electrodes. Many applications will require the electrode to selectively activate many smaller populations of axons within a common nerve trunk. The purpose of this study is to computationally model the performance of a flat interface nerve electrode (FINE) on the proximal femoral nerve for standing and stepping applications. Simulations investigated multiple FINE configurations to determine the optimal number and locations of contacts for the maximum muscular selectivity. Realistic finite element method (FEM) models were developed from digitized cross sections from cadaver femoral nerve specimens. Electrical potentials were calculated and interpolated voltages were applied to a double-cable axon model. Model output was analyzed to determine selectivity and estimate joint moments with a musculoskeletal model. Simulations indicated that a 22-contact FINE will produce the greatest selectivity. Simulations predicted that an eight-contact FINE can be expected to selectively stimulate each of the six muscles innervated by the proximal femoral nerve, producing a sufficient knee extension moment for the sit-to-stand transition and contributing 60% of the hip flexion moment needed during gait. We conclude that, whereas more contacts produce greater selectivity, eight channels are sufficient for standing and stepping with an FES system using a FINE on the common femoral nerve.