Group Research Areas:

EEG Pattern Recognition
This project aims to improve performance of NASA missions by developing brain-computer interface (BCI) technologies for augmented human-system interaction. BCI technologies will add completely new modes of interaction, which operate in parallel with keyboards, speech, or other manual controls, thereby increasing the bandwidth of human-system interaction. The research will extend recent feasibility demonstrations of electromyographic (EMG) methods for neurocontrol to the domain of electroencephalographic (EEG) methods of neurocontrol. These methods will bypass muscle activity and draw control signals directly from the human brain. BCI technologies will provide powerful and intuitive modes of interaction with 2-D and 3-D data, particularly for visualization and searching in complex data structures, such as geographical maps, satellite images, and terrain databases.

EMG Pattern Recognition
Electromyogram (EMG) signals are representative of the electrical energy present during muscle activation. These signals are may be sensed non-invasively by placing sensors on the skin which form a low impedance electrical connection with the tissue. These sensors can be either wet or dry, where the wet sensors use a conductive gel between the electrode and skin. We have developed pattern recognition software which can recognize EMG signals resulting from specific hand gestures. Examples of these gestures include pretending to move a joystick and pretending to type. We are thus able to "type" and use joysticks without having the mechanical joystick and keyboard devices physically present. Our future work includes developing improved electrodes, and further research and development into algorithms intrinsic to adaptive time-series analysis.