Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
about
Computational neurorehabilitation: modeling plasticity and learning to predict recoveryfNIRS-based brain-computer interfaces: a reviewDetection and classification of three-class initial dips from prefrontal cortex.Comparison of Brain Activation during Motor Imagery and Motor Movement Using fNIRSApplications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation.Single-trial lie detection using a combined fNIRS-polygraph system.Determining Optimal Feature-Combination for LDA Classification of Functional Near-Infrared Spectroscopy Signals in Brain-Computer Interface ApplicationHybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A ReviewMental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces.Benchmarking Brain-Computer Interfaces Outside the Laboratory: The Cybathlon 2016.Wearable and modular functional near-infrared spectroscopy instrument with multidistance measurements at four wavelengths.A Novel Method for Classifying Driver Mental Workload Under Naturalistic Conditions With Information From Near-Infrared Spectroscopy
P2860
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P2860
Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
description
2013 nî lūn-bûn
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2013年の論文
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2013年論文
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2013年論文
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2013年論文
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2013年論文
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2013年論文
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2013年论文
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2013年论文
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2013年论文
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name
Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
@en
type
label
Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
@en
prefLabel
Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
@en
P2093
P2860
P356
P1476
Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
@en
P2093
Janis Edelmann
Marie-Christine Fluet
Martin Wolf
Olivier Lambercy
Raphael Zimmermann
Robert Riener
P2860
P2888
P356
10.1186/1743-0003-10-4
P577
2013-01-21T00:00:00Z