Decoding of velocities and positions of 3D arm movement from EEG.
A brain-computer interface (BCI) can be used to control a limb neuroprosthesis with motor imaginations (MI) to restore limb functionality of paralyzed persons. However, existing BCIs lack a natural control and need a considerable amount of training time or use invasively recorded biosignals. We show that it is possible to decode velocities and positions of executed arm movements from electroencephalography signals using a new paradigm without external targets. This is a step towards a non-invasive BCI which uses natural MI. Furthermore, training time will be reduced, because it is not necessary to learn new mental strategies.
Institute of Knowledge Discovery, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria. patrick.ofner@tugraz.at
Patrick
P
Ofner
Gernot R
GR
Müller-Putz
D001132:Arm / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D009068:Movement; D012016:Reference Values