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Brain-computer interfaces (BCI) offer potential for individuals with a variety of motor and sensory disabilities to control their environment, communicate, and control mobility aids. However, the key to BCI usability rests in being able to extract relevant time varying signals that can be classified into usable commands in real time. This paper reports the first success of the Strathclyde BCI controlling...
In this paper, we present the results of single trial EEG classification of observed wrist movements. This study is part of our endeavour to develop brain computer interfaces as an assistive device for people with severe motor disabilities. Our methods rely on a simple but robust algorithm that requires no subject training to modulate brain activity. We adopt a method based on extraction and selection...
Brain-computer interfaces (BCI) offer potential for individuals with a variety of movement and sensory disabilities to control their environment, communicate and control mobility aids. However, the key to BCI usability rests in being able to extract relevant time varying signals that can be classified into usable commands. In this study we report on the results of experiments investigating the ability...
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