title: Simultaneous scalp electroencephalography (EEG), electromyography (EMG), and whole-body segmental inertial recording for multi-modal neural decoding.
abstract: Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.
authors.affiliation: Functional and Applied Biomechanics Group, National Institutes of Health, Bethesda, MD, USA. thomas.bulea@nih.gov
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Bulea
authors.forename: Atilla
authors.initials: A
authors.lastname: Kilicarslan
authors.forename: Recep
authors.initials: R
authors.lastname: Ozdemir
authors.forename: William H
authors.initials: WH
authors.lastname: Paloski
authors.forename: Jose L
authors.initials: JL
authors.lastname: Contreras-Vidal
mesh_terms: D001696:Biomechanical Phenomena; D001921:Brain / Q000502:physiology*; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D005684:Gait / Q000502:physiology*; D006801:Humans; D009474:Neurons / Q000502:physiology*; D016138:Walking / Q000502:physiology*
references.citation: Neuroimage. 2012 Nov 15;63(3):1203-11
references.pmid: 22906791
references.citation: J Neurophysiol. 2011 Oct;106(4):1875-87
references.pmid: 21768121
references.citation: Sensors (Basel). 2011;11(6):5819-34
references.pmid: 22163929
references.citation: J Neurophysiol. 2012 Jul;108(1):18-24
references.pmid: 22496527
references.citation: IEEE Trans Neural Syst Rehabil Eng. 2012 Mar;20(2):212-9
references.pmid: 22438336
references.citation: Med Biol Eng Comput. 2005 Mar;43(2):273-82
references.pmid: 15865139
references.citation: J Appl Physiol (1985). 2004 Apr;96(4):1486-95
references.pmid: 15016793
references.citation: Int J Psychophysiol. 2009 Aug;73(2):95-100
references.pmid: 19414039
references.citation: J Neurophysiol. 2010 Jun;103(6):3526-34
references.pmid: 20410364
references.citation: J Physiol. 2012 May 15;590(10):2443-52
references.pmid: 22393252
references.citation: Front Integr Neurosci. 2009 Mar 09;3:3
references.pmid: 19404411
references.citation: J Neurosci Methods. 2004 Mar 15;134(1):9-21
references.pmid: 15102499
references.citation: Nat Neurosci. 2007 Aug;10(8):1055-62
references.pmid: 17603479
references.citation: Rev Neurosci. 2011;22(6):593-608
references.pmid: 22070621
references.citation: Exp Brain Res. 2009 Mar;193(3):445-54
references.pmid: 19030850
references.citation: Brain Res Rev. 2008 Jan;57(1):2-12
references.pmid: 17916382
references.citation: J Vis Exp. 2009 Jul 29;(29):
references.pmid: 19641479
references.citation: Neuroimage. 2011 Jan 15;54(2):1289-96
references.pmid: 20832484
references.citation: J Neurosci Methods. 2006 Oct 30;157(2):337-54
references.pmid: 16777232
references.citation: J Vis Exp. 2011 May 23;(51):
references.pmid: 21654620