Decoding of continuous movement attempt in 2-dimensions from non-invasive low frequency brain signals

Gernot Müller-Putz, Valeria Mondini, Víctor Martínez-Cagigal, Reinmar Kobler, Joana Pereira, Catarina Lopes-Dias, Lea Hehenberger, Andreea Ioana Sburlea

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

Decoding intended movements from individuals with spinal cord injury (SCI) has been a central topic in braincomputer interface research for decades. Recent works, relying on neural spiking activity, demonstrated that the kinematics of
intended movements can be detected in neural spiking activity and used by individuals with SCI to control end-effectors.
Whether, and to which degree this approach translates to EEG remains an open question. In this work, we summarize our attempts towards realizing an EEG-based movement decoder.
We summarize our efforts to address this topic from various perspectives, and we present results of a single case study with a non-disabled participant, where we decoded the intended movement trajectories, while the participant’s arm was fixed
Originalspracheenglisch
Titel2021 10th International IEEE/EMBS Conference on Neural Engineering, NER 2021
Seiten322-325
ISBN (elektronisch)9781728143378
DOIs
PublikationsstatusVeröffentlicht - 4 Mai 2021
Veranstaltung10th International IEEE/EMBS Conference on Neural Engineering - Virtuell
Dauer: 4 Mai 20216 Mai 2021

Konferenz

Konferenz10th International IEEE/EMBS Conference on Neural Engineering
KurztitelNER '21
OrtVirtuell
Zeitraum4/05/216/05/21

ASJC Scopus subject areas

  • Artificial intelligence
  • Maschinenbau

Fingerprint

Untersuchen Sie die Forschungsthemen von „Decoding of continuous movement attempt in 2-dimensions from non-invasive low frequency brain signals“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren