Non-linear online low-frequency EEG decoding of arm movements during a pursuit tracking task

Víctor Martínez-Cagigal, Reinmar Kobler, Valeria Mondini, Roberto Hornero, Gernot Müller-Putz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Decoding upper-limb movements in invasive recordings has become a reality, but neural tuning in non-invasive low-frequency recordings is still under discussion. Recent studies managed to decode movement positions and velocities using linear decoders, even developing an online system. The decoded signals, however, exhibited smaller amplitudes than actual movements, affecting feedback and user experience. Recently, we showed that a non-linear offline decoder can combine directional (e.g., velocity) and non-directional (e.g., speed) information. In this study, it is assessed if the non-linear decoder can be used online to provide real-time feedback. Five healthy subjects were asked to track a moving target by controlling a robotic arm. Initially, the robot was controlled by their right hand; then, the control was gradually switched until it was entirely controlled by the electroencephalogram (EEG). Correlations between actual and decoded movements were generally above chance level. Results suggest that information about speed was also encoded in the EEG, demonstrating that the proposed non-linear decoder is suitable for decoding real-time arm movements.

Original languageEnglish
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
Pages2981-2985
Number of pages5
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - 20 Jul 2020
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society - Virtuell, Canada
Duration: 20 Jul 202024 Jul 2020

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleEMBC 2020
CountryCanada
CityVirtuell
Period20/07/2024/07/20

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  • Cite this

    Martínez-Cagigal, V., Kobler, R., Mondini, V., Hornero, R., & Müller-Putz, G. (2020). Non-linear online low-frequency EEG decoding of arm movements during a pursuit tracking task. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 2981-2985) https://doi.org/10.1109/EMBC44109.2020.9175723