Kinematic state feedback is important for neuroprostheses to generate stable and adaptive
movements of an extremity. State information, represented in the firing rates of populations …

Sensory feedback is required by biological motor control systems to maintain stability,
respond to perturbations, and adapt. Similarly, motor neuroprostheses require feedback to …

Model-based decoding of neural activity for neuroprosthetic systems has been shown, in
simulation, to provide significant gain over traditional linear filter approaches. We tested the …

Neural motor prostheses (NMPs) require the accurate decoding of motor cortical population
activity for the control of an artificial motor system. Previous work on cortical decoding for …

The prospect of assisting disabled patients by translating neural activity from the brain into
control signals for prosthetic devices, has flourished in recent years. Current systems rely on …

By decoding neural activity into useful behavioral commands, neural prosthetic systems
seek to improve the lives of severely disabled human patients. Motor decoding algorithms …

We assessed the ability of two algorithms to predict hand kinematics from neural activity as a
function of the amount of data used to determine the algorithm parameters. Using chronically …

When designing neuroprosthetic interfaces for motor function, it is crucial to have a system
that can extract reliable information from available neural signals and produce an output …

Objective. Providing accurate and robust estimates of limb kinematics from recorded neural
activities is prominent in closed-loop control of functional electrical stimulation (FES). A …

In this paper we introduce a theoretical framework for improved processing of peri-
movement neural activity for neurally controlled prosthetic systems through maximum …