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A brain-machine interface model based on EEG for automated navigation of mobile robotic device
The highly parallel neurophysiological recordings and the increasing number of signal processing tools open up new avenues for connecting technologies directly to neuronal processes. As the understanding of the neuronal signals is taking a better shape, lot more work to perform is coming up to properly interpret and use these signals for brain-machine interfaces. A simple brain-machine interface may be able to reestablish the broken loop of the persons with motor dysfunction. With time the brain-machine interfacing is growing more complex due to the increased availability of instruments and processes for implementation. In this work, the author proposes a brain-machine interface model through a few simple processes for automated navigation and control of robotic device using the extracted features from the EEG signals based on saccadic eye movement tasks
EEG Based Brain-Machine Interface for Navigation of Robotic Device
The highly parallel neurophysiological recordings
and the increasing number of signal processing tools open up
new avenues for connecting technologies directly to neuronal
processes. As the understanding of the neuronal signals is
taking a better shape, lot more work to perform is coming up to
properly interpret and use these signals for brain-machine
interfaces. A simple brain-machine interface may be able to
reestablish the broken loop of the persons with motor
dysfunction. With time the brain-machine interfacing is
growing more complex due to the increased availability of
instruments and processes for implementation. In this work,
the author proposes a brain-machine interface model through a
few simple processes for automated navigation and control of
robotic device using the extracted features from the EEG
signals based on saccadic eye movement tasks
An integrated tool for quantification of dynamic PET studies: Spectral Analysis Kinetic Estimation
Novel hierarchical approach for voxel-wise PET quantification: application on multi-compartmental models
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