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Multimodal neuroelectric interface development

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9 Author(s)
L. J. Trejo ; NASA Ames Res. Center, Moffett Field, CA, USA ; K. R. Wheeler ; C. C. Jorgensen ; R. Rosipal
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We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

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IEEE Transactions on Neural Systems and Rehabilitation Engineering  (Volume:11 ,  Issue: 2 )