<div><p>In patients with unilateral upper limb paralysis from strokes and other brain lesions, strategies for functional recovery may eventually include brain-machine interfaces (BMIs) using control signals from residual sensorimotor systems in the damaged hemisphere. When voluntary movements of the contralateral limb are not possible due to brain pathology, initial training of such a BMI may require use of the unaffected ipsilateral limb. We conducted an offline investigation of the feasibility of decoding ipsilateral upper limb movements from electrocorticographic (ECoG) recordings in three patients with different lesions of sensorimotor systems associated with upper limb control. We found that the first principal component (PC) of uncons...
Today, learning from the brain is the most challenging issue in many areas. Neural scientists, compu...
Brain machine interfaces (BMIs) have the potential to provide intuitive control of neuroprostheses t...
Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb p...
In patients with unilateral upper limb paralysis from strokes and other brain lesions, strategies fo...
Brain-machine interface (BMI) technology aims to provide individuals with movement paralysis a natur...
Abstract — Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially control u...
Several motor related Brain Computer Interfaces (BCIs) have been developed over the years that use a...
Brain-computer interface (BCI) systems have emerged as a method to restore function and enhance comm...
OBJECTIVE: Brain-computer interface (BCI) technology aims to provide individuals with paralysis a me...
The discovery of directional tuned neurons in the primary motor cortex has advanced motor research i...
In Brain-Computer Interfacing (BCI), brain activity is translated into actions that communicate the ...
Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishin...
Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control ...
Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals ...
Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals ...
Today, learning from the brain is the most challenging issue in many areas. Neural scientists, compu...
Brain machine interfaces (BMIs) have the potential to provide intuitive control of neuroprostheses t...
Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb p...
In patients with unilateral upper limb paralysis from strokes and other brain lesions, strategies fo...
Brain-machine interface (BMI) technology aims to provide individuals with movement paralysis a natur...
Abstract — Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially control u...
Several motor related Brain Computer Interfaces (BCIs) have been developed over the years that use a...
Brain-computer interface (BCI) systems have emerged as a method to restore function and enhance comm...
OBJECTIVE: Brain-computer interface (BCI) technology aims to provide individuals with paralysis a me...
The discovery of directional tuned neurons in the primary motor cortex has advanced motor research i...
In Brain-Computer Interfacing (BCI), brain activity is translated into actions that communicate the ...
Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishin...
Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control ...
Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals ...
Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals ...
Today, learning from the brain is the most challenging issue in many areas. Neural scientists, compu...
Brain machine interfaces (BMIs) have the potential to provide intuitive control of neuroprostheses t...
Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb p...