Cortical control of a prosthetic arm for self-feeding

  title={Cortical control of a prosthetic arm for self-feeding},
  author={Meel Velliste and Sagi Perel and M. Chance Spalding and Andrew S. Whitford and Andrew B. Schwartz},
Arm movement is well represented in populations of neurons recorded from the motor cortex. Cortical activity patterns have been used in the new field of brain–machine interfaces to show how cursors on computer displays can be moved in two- and three-dimensional space. Although the ability to move a cursor can be useful in its own right, this technology could be applied to restore arm and hand function for amputees and paralysed persons. However, the use of cortical signals to control a multi… 

Brain–machine interfaces: Getting to grips with a robotic arm

  • K. Whalley
  • Biology, Psychology
    Nature Reviews Neuroscience
  • 2008
The task that was completed by the monkeys was more complicated and demanding than those that have previously been attempted and more closely resembled a real-life situation, representing a significant advance in the technology of brain–machine interfaces.

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

The 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.

Motor Cortical Correlates of Arm Resting in the Context of a Reaching Task and Implications for Prosthetic Control

The concept of motor-cortical function is expanded by showing that population activity reflects behavioral context in addition to the direct parameters of the movement itself by predicting zero velocity correctly, which would avoid undesired motion in a prosthetic application.

Brain-Computer Interface Control of an Anthropomorphic Robotic Arm

A brain-computer interface system to allow direct cortical control of 7 active degrees of freedom in a robotic arm was developed and two monkeys with chronic microelectrode implants in their motor cortices were able to use the arm to complete an oriented grasping task under brain control.

A Brain-Machine Interface Enables Bimanual Arm Movements in Monkeys

A bimanual BMI that enables rhesus monkeys to control two avatar arms simultaneously and widespread plasticity in frontal and parietal cortical areas is observed, suggesting that cortical networks may assimilate the two avatar Arms through BMI control.

Neural response to grasp of robot hand from M1 area of Rhesus monkey

It is shown that neural decoder based on observation could be used for reaching to grasp type brain-machine interface in human especially for grasping and there were neuronal groups showing increased activities for each time periods.

A brain-computer interface that evokes tactile sensations improves robotic arm control

This work supplemented vision with tactile percepts evoked using a bidirectional brain-computer interface that records neural activity from the motor cortex and generates tactile sensations through intracortical microstimulation of the somatosensory cortex, enabling a person with tetraplegia to substantially improve performance with a robotic limb.

Neural Correlates of Learning in Brain Machine Interface Controlled Tasks

The results suggest that information and trajectories in the neural space increase after initially introducing the perturbations, and before the subject settles into workable solutions.

Generalized virtual fixtures for shared-control grasping in brain-machine interfaces

A new method of "Positive-Span" Virtual Fixturing extends the concept of Virtual Fixtures to guide both translational and rotational DoF of a brain-controlled robot hand toward whole sets of robot poses that would allow an object to be grasped.

Brain-machine interfaces: assistive, thought-controlled devices

study, monkeys were trained to operate robotic wheelchairs via wireless BMI could provide fairly accurate predictions of arm motions made by the animals. This neuronal ‘tuning’ is the crux of BMI



Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates

It is demonstrated that primates can learn to reach and grasp virtual objects by controlling a robot arm through a closed-loop brain–machine interface (BMIc) that uses multiple mathematical models to extract several motor parameters from the electrical activity of frontoparietal neuronal ensembles.

The general utility of a neuroprosthetic device under direct cortical control

We have described an adaptive signal processing method that allows fine graded control of a cursor in three-dimensions from cortical signals. Here we describe application of the same signal

Instant neural control of a movement signal

The results indicate that neurally based control of movement may eventually be feasible in paralysed humans and show how activity from a few MI neurons can be decoded into a signal that a monkey is able to use immediately to move a computer cursor to any new position in its workspace.

Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

The results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.

Motor cortical representation of speed and direction during reaching.

The motor cortical substrate associated with reaching was studied as monkeys moved their hands from a central position to one of eight targets spaced around a circle, and the distributions of preferred directions were found to be significantly different from cortical activity.

Neuronal ensemble control of prosthetic devices by a human with tetraplegia

Initial results for a tetraplegic human using a pilot NMP suggest that NMPs based upon intracortical neuronal ensemble spiking activity could provide a valuable new neurotechnology to restore independence for humans with paralysis.

Cortical Ensemble Adaptation to Represent Velocity of an Artificial Actuator Controlled by a Brain-Machine Interface

It is shown that rapid modifications in neuronal representation of velocity of the hand and actuator occur in multiple cortical areas during the operation of a BMI, and that, during BMI control, cortical ensembles represent behaviorally significant motor parameters, even if these are not associated with movements of the animal's own limb.

Cortical neural prosthetics.

Control of prostheses using cortical signals is based on chronic microelectrode arrays, extraction algorithms, and prosthetic effectors and has the capability of restoring much of the arm movement lost with immobilizing deficits.

Selection and parameterization of cortical neurons for neuroprosthetic control

A method that allows rapid tuning of a population vector-based system for neural control without arm movements and it is feasible to parameterize control systems without any overt behaviors and that subsequent control system design will be enhanced with cautious unit selection is described.

Cognitive Control Signals for Neural Prosthetics

Higher level signals related to the goals of movements were decoded from three monkeys and used to position cursors on a computer screen without the animals emitting any behavior, improving their performance over a period of weeks.