<p>(A–F) Neural sources involved in encoding hand kinematic projected onto sagittal MRI slices, with dotted lines indicating the source location with the greatest contribution. Contralateral motor regions of the brain provided the greatest contribution in the decoding models with 26, 25 and 23 sensors. No motor related brain region is involved in the other decoding models. (G–H) Distributions of (G) and (H) for all participants for decoding models built by progressive elimination of electrodes. These results indicate that significant similar results were obtained in the decoding models that utilize 26, 25, 23, 21 and 17 electrodes, but the results were significantly different and lower when utilizing 14 and 11 electrodes.</p
Abstract Background Intracortical brain–machine interfaces (BMIs) harness movement information by se...
Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb p...
Decoding neural signals into control outputs has been a key to the development of brain-computer int...
<p>Top: Location of the electrodes (black dots) used to built the decoding model and the removed ele...
Using brain activity directly as input for assistive tool control can circumvent muscular dysfunctio...
Abstract — The direct neural control of external prosthetic devices such as robot hands requires the...
ObjectiveElectrocorticography (ECoG)-based brain-computer interface (BCI) is a promising platform fo...
We performed “virtual lesions” in the predictors of decoding models, by ablating either anatomical (...
The possibility of controlling dexterous hand prostheses by using a direct connection with the nervo...
Brain-Computer Interfaces (BCIs) that decode a patient's movement intention to control a prosthetic ...
Abstract—A direct comparison of the decoding performance of EEG and MEG in respect of hand movements...
In recent years, technology has allowed the progressive increase in the number of channels for EEG r...
<p><b>A.1–A.2</b>: Decay rate after the stimulation for sham and stimulation condition in the comput...
Abstract — By decoding neural activity into useful behavioral commands, neural prosthetic systems se...
Neural prosthetic technology has moved from the laboratory to clinical settings with human trials. T...
Abstract Background Intracortical brain–machine interfaces (BMIs) harness movement information by se...
Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb p...
Decoding neural signals into control outputs has been a key to the development of brain-computer int...
<p>Top: Location of the electrodes (black dots) used to built the decoding model and the removed ele...
Using brain activity directly as input for assistive tool control can circumvent muscular dysfunctio...
Abstract — The direct neural control of external prosthetic devices such as robot hands requires the...
ObjectiveElectrocorticography (ECoG)-based brain-computer interface (BCI) is a promising platform fo...
We performed “virtual lesions” in the predictors of decoding models, by ablating either anatomical (...
The possibility of controlling dexterous hand prostheses by using a direct connection with the nervo...
Brain-Computer Interfaces (BCIs) that decode a patient's movement intention to control a prosthetic ...
Abstract—A direct comparison of the decoding performance of EEG and MEG in respect of hand movements...
In recent years, technology has allowed the progressive increase in the number of channels for EEG r...
<p><b>A.1–A.2</b>: Decay rate after the stimulation for sham and stimulation condition in the comput...
Abstract — By decoding neural activity into useful behavioral commands, neural prosthetic systems se...
Neural prosthetic technology has moved from the laboratory to clinical settings with human trials. T...
Abstract Background Intracortical brain–machine interfaces (BMIs) harness movement information by se...
Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb p...
Decoding neural signals into control outputs has been a key to the development of brain-computer int...