High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
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Control strategies for active lower extremity prosthetics and orthotics: a review.Control of an Ambulatory Exoskeleton with a Brain-Machine Interface for Spinal Cord Injury Gait RehabilitationYour Brain on Art: Emergent Cortical Dynamics During Aesthetic Experiences.Neural decoding of expressive human movement from scalp electroencephalography (EEG).Risk management and regulations for lower limb medical exoskeletons: a review.Applications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation.A simple ERP method for quantitative analysis of cognitive workload in myoelectric prosthesis control and human-machine interactionSitting and standing intention can be decoded from scalp EEG recorded prior to movement executionA convolutional neural network for steady state visual evoked potential classification under ambulatory environment.A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants.Negligible Motion Artifacts in Scalp Electroencephalography (EEG) During Treadmill Walking.Training Persons with Spinal Cord Injury to Ambulate Using a Powered Exoskeleton.Classification of stand-to-sit and sit-to-stand movement from low frequency EEG with locality preserving dimensionality reduction.A Closed-loop Brain Computer Interface to a Virtual Reality Avatar: Gait Adaptation to Visual Kinematic Perturbations.Decoding Lower Limb Muscle Activity and Kinematics from Cortical Neural Spike Trains during Monkey Performing Stand and Squat Movements.Methodological aspects of EEG and body dynamics measurements during motion.Identifying Engineering, Clinical and Patient's Metrics for Evaluating and Quantifying Performance of Brain-Machine Interface (BMI) Systems.Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation.Electrocortical activity distinguishes between uphill and level walking in humans.A Biomechanical Comparison of Proportional Electromyography Control to Biological Torque Control Using a Powered Hip Exoskeleton.Real-time EEG-based brain-computer interface to a virtual avatar enhances cortical involvement in human treadmill walkingMultiple Kernel Based Region Importance Learning for Neural Classification of Gait States from EEG Signals.The Myosuit: Bi-articular Anti-gravity Exosuit That Reduces Hip Extensor Activity in Sitting Transfers.Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain-computer interface to a virtual reality avatar.Electrocortical correlates of human level-ground, slope, and stair walking.Biomechanics and energetics of walking in powered ankle exoskeletons using myoelectric control versus mechanically intrinsic control.EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots
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P2860
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
@pt
bilimsel makale
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scientific article published on January 2013
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
@en
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
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type
label
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
@en
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
@nl
prefLabel
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
@en
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
@nl
P2093
P2860
P1476
High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton
@en
P2093
Atilla Kilicarslan
Robert G Grossman
Saurabh Prasad
P2860
P304
P356
10.1109/EMBC.2013.6610821
P407
P577
2013-01-01T00:00:00Z