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.