Single trial prediction of self-paced reaching directions from EEG signals

Early detection of movement intention could possibly minimize the delays in the activation of neuroprosthetic devices. As yet, single trial analysis using non-invasive approaches for understanding such movement preparation remains a challenging task. We studied the feasibility of predicting movement...

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Main Authors: Eileen Yi Lee Lew, Ricardo eChavarriaga, Stefano eSilvoni, José del R eMillán
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-08-01
Series:Frontiers in Neuroscience
Subjects:
EEG
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00222/full
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spelling doaj-2bee9b6b7cf043779059debac6fb18c12020-11-25T00:19:39ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2014-08-01810.3389/fnins.2014.0022291092Single trial prediction of self-paced reaching directions from EEG signalsEileen Yi Lee Lew0Eileen Yi Lee Lew1Ricardo eChavarriaga2Stefano eSilvoni3José del R eMillán4Ecole Polytechnique Fédérale de LausanneUniversity of LausanneEcole Polytechnique Fédérale de LausanneI.R.R.C.S. S.Camillo Hospital FoundationEcole Polytechnique Fédérale de LausanneEarly detection of movement intention could possibly minimize the delays in the activation of neuroprosthetic devices. As yet, single trial analysis using non-invasive approaches for understanding such movement preparation remains a challenging task. We studied the feasibility of predicting movement directions in self-paced upper limb center-out reaching tasks, i.e., spontaneous movements executed without an external cue that can better reflect natural motor behavior in humans. We reported results of non-invasive electroencephalography (EEG) recorded from mild stroke patients and able-bodied participants. Previous studies have shown that low frequency EEG oscillations are modulated by the intent to move and therefore, can be decoded prior to the movement execution. Motivated by these results, we investigated whether slow cortical potentials (SCPs) preceding movement onset can be used to classify reaching directions and evaluated the performance using 5-fold cross-validation. For able-bodied subjects, we obtained an average decoding accuracy of 76% (chance level of 25%) at 62.5ms before onset using the amplitude of on-going SCPs with above chance level performances between 875ms to 437.5ms prior to onset. The decoding accuracy for the stroke patients was on average 47% with their paretic arms. Comparison of the decoding accuracy across different frequency ranges (i.e., SCPs, delta, theta, alpha and gamma) yielded the best accuracy using SCPs filtered between 0.1 to 1 Hz. Across all the subjects, including stroke subjects, the best selected features were obtained mostly from the fronto-parietal regions, hence consistent with previous neurophysiological studies on arm reaching tasks. In summary, we concluded that SCPs allow the possibility of single trial decoding of reaching directions at least 312.5ms before onset of reach.http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00222/fullStrokeEEGBrain-machine interface (BMI)movement directionSelf-paced voluntary movementMovement-related Potentials
collection DOAJ
language English
format Article
sources DOAJ
author Eileen Yi Lee Lew
Eileen Yi Lee Lew
Ricardo eChavarriaga
Stefano eSilvoni
José del R eMillán
spellingShingle Eileen Yi Lee Lew
Eileen Yi Lee Lew
Ricardo eChavarriaga
Stefano eSilvoni
José del R eMillán
Single trial prediction of self-paced reaching directions from EEG signals
Frontiers in Neuroscience
Stroke
EEG
Brain-machine interface (BMI)
movement direction
Self-paced voluntary movement
Movement-related Potentials
author_facet Eileen Yi Lee Lew
Eileen Yi Lee Lew
Ricardo eChavarriaga
Stefano eSilvoni
José del R eMillán
author_sort Eileen Yi Lee Lew
title Single trial prediction of self-paced reaching directions from EEG signals
title_short Single trial prediction of self-paced reaching directions from EEG signals
title_full Single trial prediction of self-paced reaching directions from EEG signals
title_fullStr Single trial prediction of self-paced reaching directions from EEG signals
title_full_unstemmed Single trial prediction of self-paced reaching directions from EEG signals
title_sort single trial prediction of self-paced reaching directions from eeg signals
publisher Frontiers Media S.A.
series Frontiers in Neuroscience
issn 1662-453X
publishDate 2014-08-01
description Early detection of movement intention could possibly minimize the delays in the activation of neuroprosthetic devices. As yet, single trial analysis using non-invasive approaches for understanding such movement preparation remains a challenging task. We studied the feasibility of predicting movement directions in self-paced upper limb center-out reaching tasks, i.e., spontaneous movements executed without an external cue that can better reflect natural motor behavior in humans. We reported results of non-invasive electroencephalography (EEG) recorded from mild stroke patients and able-bodied participants. Previous studies have shown that low frequency EEG oscillations are modulated by the intent to move and therefore, can be decoded prior to the movement execution. Motivated by these results, we investigated whether slow cortical potentials (SCPs) preceding movement onset can be used to classify reaching directions and evaluated the performance using 5-fold cross-validation. For able-bodied subjects, we obtained an average decoding accuracy of 76% (chance level of 25%) at 62.5ms before onset using the amplitude of on-going SCPs with above chance level performances between 875ms to 437.5ms prior to onset. The decoding accuracy for the stroke patients was on average 47% with their paretic arms. Comparison of the decoding accuracy across different frequency ranges (i.e., SCPs, delta, theta, alpha and gamma) yielded the best accuracy using SCPs filtered between 0.1 to 1 Hz. Across all the subjects, including stroke subjects, the best selected features were obtained mostly from the fronto-parietal regions, hence consistent with previous neurophysiological studies on arm reaching tasks. In summary, we concluded that SCPs allow the possibility of single trial decoding of reaching directions at least 312.5ms before onset of reach.
topic Stroke
EEG
Brain-machine interface (BMI)
movement direction
Self-paced voluntary movement
Movement-related Potentials
url http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00222/full
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