Neural Interfacing with the Peripheral Nervous System: A FINE Approach

Abstract

Functional electrical stimulation (FES) can restore neural functions such as volitional motion to patients with neurological injuries or diseases, and effective and safe neural interfaces with peripheral nerves are required. Flat interface nerve electrode (FINE) enables the recording of the various signals within the cuff. The recovery of the various fascicular signals within the nerve is still a very challenging problem. The localization and the recovery of many signals pose a significant challenge due to the low signal-to-noise ratio and the large number of fascicles. FINE also allows selective control of different muscles at the same time. Yet, motion control of neuromuscular skeletal systems using multi-contact electrodes remains an unsolved and difficult problem due to the complexities of the systems and the large number of channels required to activate the various muscles involved in the motion. Using computer models of the peripheral nerve, we have tested the ability of various algorithms to control the neuromuscular skeletal dynamics. Computer models have also been used to develop new methods to recover fascicular signals within the nerve. Both the control and the detection algorithms have been tested experimentally and preliminary results are included. The goal of this review is to examine the possibility of detecting peripheral nerve signals and use these voluntary signals to restore functions in patients with stroke, amputation or paralysis.