Hand movement decoding by phase-locking low frequency EEG signals

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 hypothe...

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Hauptverfasser:	Jiaen Liu, Perdoni, C., Bin He
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adult Algorithms Biomechanical Phenomena Brain - pathology Brain modeling Correlation Decoding Electrodes Electroencephalography Electroencephalography - methods Equipment Design Extremities - pathology Female Hand - physiology Helium Humans Kinematics Male Models, Statistical Movement Neurons - pathology Regression Analysis Self-Help Devices Signal Processing, Computer-Assisted Time Factors User-Computer Interface
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Beschreibung
Zusammenfassung:	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 (
ISSN:	1094-687X 1557-170X 1558-4615
DOI:	10.1109/IEMBS.2011.6091564