Being noninvasive, low-risk and inexpensive, EEG is a promising methodology in the application of human Brain Computer Interface (BCI) to help those with motor dysfunctions. Here we employed a center-out task paradigm to study the decoding of hand velocity in the EEG recording. We tested the hypothesis using a linear regression model and found a significant correlation between velocity and the low-pass filtered EEG signal (2 Hz). The low-pass filtered EEG was not only tuned to the direction but also phase-locked to the amplitude of velocity. This suggests an EEG form of the neuronal population vector theory, which is considered to encode limb kinematic information, and provides a new method of BCI implementation.
|Original language||English (US)|
|Number of pages||4|
|Journal||Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference|
|State||Published - 2011|
|Event||33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States|
Duration: Aug 30 2011 → Sep 3 2011