Decoding movement intent

Decoding movement intent

A key consideration in the development of any BCI is how to give the user the ability to start and stop operating the device. In the case of a speech-synthesizer based BCI, being able to pause the device will be critical to the intelligibility of the output. Perhaps the most intuitive solution is to decode the user’s intent directly, incorporating the classification of [intent to operate vs. rest] in the BCI decoder itself. Along these lines, we have been investigating computational techniques for classifying imagined hand and speech articulator movements from a resting state in real time.

Main personnel Emily Stephen Funding:
Collaborators Jon Brumberg, Frank Guenther NIH/NIDCD: Decoding imagined vowel productions using electroencephalography 

NIH/NIDCD: Neural modeling and imaging in speech