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With the goal of providing a speech prosthesis for individuals with severe communication impairments, we propose a control scheme for brain-computer interfaces using vowel speech imagery. Electroencephalography was recorded in three healthy subjects for three tasks, imaginary speech of the English vowels /a/ and /u/, and a no action state as control. Trial(More)
The ability to reconstruct muscle activity time series from electroencephalography (EEG) may lead to drastic improvements in brain-machine interfaces (BMIs) by providing a means for realistic continuous reproduction of dexterous movements in human beings. However, it is considered difficult to isolate signals related to individual muscle activities from EEG(More)
Brain-computer interfaces (BCIs) offer a potential means to replace or restore lost motor function. However, BCI performance varies considerably between users, the reasons for which are poorly understood. Here we investigated the relationship between sensorimotor rhythm (SMR)-based BCI performance and brain structure. Participants were instructed to control(More)
With the purpose of providing assistive technology for the communication impaired, we propose a control algorithm for speech prostheses using vowel speech imagery. Electroen-cephalograms were recorded in three healthy subjects during the performance of three tasks, imaginary speech of the English vowels /a/ and /u/, and a no action state as control. Speech(More)
There is a growing interest in how the brain transforms body part positioning in the extrinsic environment into an intrinsic coordinate frame during motor control. To explore the human brain areas representing intrinsic and extrinsic coordinate frames, this fMRI study examined neural representation of motor cortices while human participants performed(More)
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