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Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control

Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which bu...

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Autores principales: Müller-Putz, Gernot R., Kobler, Reinmar J., Pereira, Joana, Lopes-Dias, Catarina, Hehenberger, Lea, Mondini, Valeria, Martínez-Cagigal, Víctor, Srisrisawang, Nitikorn, Pulferer, Hannah, Batistić, Luka, Sburlea, Andreea I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961864/
https://www.ncbi.nlm.nih.gov/pubmed/35360289
http://dx.doi.org/10.3389/fnhum.2022.841312
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author Müller-Putz, Gernot R.
Kobler, Reinmar J.
Pereira, Joana
Lopes-Dias, Catarina
Hehenberger, Lea
Mondini, Valeria
Martínez-Cagigal, Víctor
Srisrisawang, Nitikorn
Pulferer, Hannah
Batistić, Luka
Sburlea, Andreea I.
author_facet Müller-Putz, Gernot R.
Kobler, Reinmar J.
Pereira, Joana
Lopes-Dias, Catarina
Hehenberger, Lea
Mondini, Valeria
Martínez-Cagigal, Víctor
Srisrisawang, Nitikorn
Pulferer, Hannah
Batistić, Luka
Sburlea, Andreea I.
author_sort Müller-Putz, Gernot R.
collection PubMed
description Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which build the basis for enabling severely paralyzed people to non-invasively control a robotic arm in real-time from electroencephalogram (EEG). In detail, we investigated goal-directed movement detection, decoding of executed and attempted movement trajectories, grasping correlates, error processing, and kinesthetic feedback. Although we have tested some of our approaches already with the target populations, we still need to transfer the “Feel Your Reach” framework to people with cervical spinal cord injury and evaluate the decoders’ performance while participants attempt to perform upper-limb movements. While on the one hand, we made major progress towards this ambitious goal, we also critically discuss current limitations.
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spelling pubmed-89618642022-03-30 Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control Müller-Putz, Gernot R. Kobler, Reinmar J. Pereira, Joana Lopes-Dias, Catarina Hehenberger, Lea Mondini, Valeria Martínez-Cagigal, Víctor Srisrisawang, Nitikorn Pulferer, Hannah Batistić, Luka Sburlea, Andreea I. Front Hum Neurosci Human Neuroscience Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which build the basis for enabling severely paralyzed people to non-invasively control a robotic arm in real-time from electroencephalogram (EEG). In detail, we investigated goal-directed movement detection, decoding of executed and attempted movement trajectories, grasping correlates, error processing, and kinesthetic feedback. Although we have tested some of our approaches already with the target populations, we still need to transfer the “Feel Your Reach” framework to people with cervical spinal cord injury and evaluate the decoders’ performance while participants attempt to perform upper-limb movements. While on the one hand, we made major progress towards this ambitious goal, we also critically discuss current limitations. Frontiers Media S.A. 2022-03-11 /pmc/articles/PMC8961864/ /pubmed/35360289 http://dx.doi.org/10.3389/fnhum.2022.841312 Text en Copyright © 2022 Müller-Putz, Kobler, Pereira, Lopes-Dias, Hehenberger, Mondini, Martínez-Cagigal, Srisrisawang, Pulferer, Batistić and Sburlea. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Human Neuroscience
Müller-Putz, Gernot R.
Kobler, Reinmar J.
Pereira, Joana
Lopes-Dias, Catarina
Hehenberger, Lea
Mondini, Valeria
Martínez-Cagigal, Víctor
Srisrisawang, Nitikorn
Pulferer, Hannah
Batistić, Luka
Sburlea, Andreea I.
Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control
title Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control
title_full Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control
title_fullStr Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control
title_full_unstemmed Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control
title_short Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control
title_sort feel your reach: an eeg-based framework to continuously detect goal-directed movements and error processing to gate kinesthetic feedback informed artificial arm control
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961864/
https://www.ncbi.nlm.nih.gov/pubmed/35360289
http://dx.doi.org/10.3389/fnhum.2022.841312
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