Decoding Movements of the Upper Limb from EEG

Research output: Contribution to conferencePoster

Abstract

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.
Original languageEnglish
Publication statusPublished - 20 Jun 2017
EventcuttingEEG - Glasgow, United Kingdom
Duration: 19 Jun 201722 Jun 2017

Workshop

WorkshopcuttingEEG
CountryUnited Kingdom
CityGlasgow
Period19/06/1722/06/17

Fields of Expertise

  • Human- & Biotechnology

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)

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    Cite this

    Ofner, P., Schwarz, A., Pereira, J., & Müller-Putz, G. (2017). Decoding Movements of the Upper Limb from EEG. Poster session presented at cuttingEEG, Glasgow, United Kingdom.