Decoding Movements of the Upper Limb from EEG

Patrick Ofner, Andreas Schwarz, Joana Pereira, Gernot Müller-Putz

Publikation: KonferenzbeitragPoster


A neuroprosthesis can restore movement functions of persons with spinal cord injury. It benefits from a brain-computer interface (BCI) with a high number of control classes. However, classical sensorimotor rhythm-based BCIs can often only provide less than 3 classes, and new types of BCIs need to be developed. We investigated whether low-frequency time-domain signals (i.e. movement-related cortical potentials) can be used to classify hand/arm movements of the same limb. A BCI based on attempted movements may be used to control a neuroprosthesis more naturally and provide a higher number of control classes.
PublikationsstatusVeröffentlicht - 20 Jun 2017
VeranstaltungcuttingEEG - Glasgow, Großbritannien / Vereinigtes Königreich
Dauer: 19 Jun 201722 Jun 2017


LandGroßbritannien / Vereinigtes Königreich

Fields of Expertise

  • Human- & Biotechnology

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)


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