Continuous neuronal ensemble control of simulated arm reaching by a human with tetraplegia

Abstract

Functional electrical stimulation (FES), the coordinated electrical activation of multiple muscles, has been used to restore arm and hand function in people with paralysis. User interfaces for such systems typically derive commands from mechanically unrelated parts of the body with retained volitional control, and are unnatural and unable to simultaneously command the various joints of the arm. Neural interface systems, based on spiking intracortical signals recorded from the arm area of motor cortex, have shown the ability to control computer cursors, robotic arms and individual muscles in intact non-human primates. Such neural interface systems may thus offer a more natural source of commands for restoring dexterous movements via FES. However, the ability to use decoded neural signals to control the complex mechanical dynamics of a reanimated human limb, rather than the kinematics of a computer mouse, has not been demonstrated. This study demonstrates the ability of an individual with long-standing tetraplegia to use cortical neuron recordings to command the real-time movements of a simulated dynamic arm. This virtual arm replicates the dynamics associated with arm mass and muscle contractile properties, as well as those of an FES feedback controller that converts user commands into the required muscle activation patterns. An individual with long-standing tetraplegia was thus able to control a virtual, two-joint, dynamic arm in real time using commands derived from an existing human intracortical interface technology. These results show the feasibility of combining such an intracortical interface with existing FES systems to provide a high-performance, natural system for restoring arm and hand function in individuals with extensive paralysis.

Computational intelligence in control

“…The first demonstration involved rats that used their brain signals to press a lever and obtain a water reward (Chapin, Moxon, Markowitz, & Nicolelis, 1999). Later, similar BMIs were demonstrated in monkeys in food reaching tasks (Wessberg et al, 2000), and more recently in humans to control cursor movement in a computer screen (Chadwick et al, 2011).…”

State-of-the-art MEMS and microsystem tools for brain research

“…This approach provides robust mechanical properties that have made it very popular in primate research [51][52][53][54] . This silicon electrode platform has been the basis for successful human trials using a brain machine interface [55][56][57] and has been adapted by several groups for wireless integration [58][59][60] .…”

Electromyography Control of a Computer Model of the Arm

“…the total (actual) distance calculated by the sum of the distances of all steps (see Equation (5) Path efficiency feedback is crucial for the arm movement [12]. Based on the straightness of the virtual arm fingertip towards the target, it becomes easy for the researcher to understand the extent to which the participants can control the movement.…”