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

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

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
Original languageEnglish
Title of host publication2021 10th International IEEE/EMBS Conference on Neural Engineering, NER 2021
Pages322-325
ISBN (Electronic)9781728143378
DOIs
Publication statusPublished - 4 May 2021
Event10th International IEEE/EMBS Conference on Neural Engineering - Virtuell
Duration: 4 May 20216 May 2021

Conference

Conference10th International IEEE/EMBS Conference on Neural Engineering
Abbreviated titleNER '21
CityVirtuell
Period4/05/216/05/21

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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