title: Selective recovery of fascicular activity in peripheral nerves.
abstract: The peripheral nerves of an amputee's residual limb still carry the information required to provide the robust, natural control signals needed to command a dexterous prosthetic limb. However, these signals are mixed in the volume conductor of the body and extracting them is an unmet challenge. A beamforming algorithm was used to leverage the spatial separation of the fascicular sources, recovering mixed pseudo-spontaneous signals with normalized mean squared error of 0.14 ± 0.10 (n = 12) in an animal model. The method was also applied to a human femoral nerve model using computer simulations and recovered all five fascicular-group signals simultaneously with R(2) = 0.7 ± 0.2 at a signal-to-noise ratio of 0 dB. This technique accurately separated peripheral neural signals, potentially providing the voluntary, natural and robust command signals needed for advanced prosthetic limbs.
authors.affiliation: Biomedical Engineering Department, Neural Engineering Center, Case Western Reserve University,Cleveland, OH, USA.
authors.forename: B
authors.initials: B
authors.lastname: Wodlinger
authors.forename: D M
authors.initials: DM
authors.lastname: Durand
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D000818:Animals; D001186:Artificial Limbs; D003198:Computer Simulation; D004558:Electric Stimulation; D004567:Electrodes, Implanted; D005071:Evoked Potentials / Q000502:physiology; D005267:Femoral Nerve / Q000502:physiology; D020342:Finite Element Analysis; D006614:Hindlimb / Q000294:innervation* / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009046:Motor Neurons / Q000502:physiology; D010525:Peripheral Nerves / Q000502:physiology*; D011474:Prosthesis Design / Q000379:methods*; D011817:Rabbits; D020127:Recovery of Function; D012584:Sciatic Nerve / Q000502:physiology; D059629:Signal-To-Noise Ratio; D013979:Tibial Nerve / Q000502:physiology