Improvement of classification accuracy in a phase-tagged steady-state visual evoked potential-based brain computer interface using multiclass support vector machine.
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Evaluation of EEG features in decoding individual finger movements from one hand.
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The brain's silent messenger: using selective attention to decode human thought for brain-based communication.
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Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface.
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The utility of multichannel local field potentials for brain-machine interfaces.
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Distributed cortical adaptation during learning of a brain-computer interface task.
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Functional priorities, assistive technology, and brain-computer interfaces after spinal cord injury.
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Spinal cord injury (SCI) often affects a person's ability to perform critical activities of daily living and can negatively affect his or her quality of life. Assistive technology aims to bridge this gap in order to augment function and increase independence. It is critical to involve consumers in the design and evaluation process as new technologies such as brain-computer interfaces (BCIs) are developed. In a survey study of 57 veterans with SCI participating in the 2010 National Veterans Wheelchair Games, we found that restoration of bladder and bowel control, walking, and arm and hand function (tetraplegia only) were all high priorities for improving quality of life. Many of the participants had not used or heard of some currently available technologies designed to improve function or the ability to interact with their environment. The majority of participants in this study were interested in using a BCI, particularly for controlling functional electrical stimulation to restore lost function. Independent operation was considered to be the most important design criteria. Interestingly, many participants reported that they would consider surgery to implant a BCI even though noninvasiveness was a high-priority design requirement. This survey demonstrates the interest of individuals with SCI in receiving and contributing to the design of BCIs. (+info)
Selective sensation based brain-computer interface via mechanical vibrotactile stimulation.
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