Characterizing relationships of DTI, fMRI, and motor recovery in stroke rehabilitation utilizing brain-computer interface technology
about
Prediction of Upper Limb Motor Recovery after Subacute Ischemic Stroke Using Diffusion Tensor Imaging: A Systematic Review and Meta-AnalysisMotor System Reorganization After Stroke: Stimulating and Training Toward PerfectionMRI Biomarkers for Hand-Motor Outcome Prediction and Therapy Monitoring following StrokeBCI-FES: could a new rehabilitation device hold fresh promise for stroke patients?DTI measures track and predict motor function outcomes in stroke rehabilitation utilizing BCI technologyDose-response relationships using brain-computer interface technology impact stroke rehabilitationBrain Plasticity following Intensive Bimanual Therapy in Children with Hemiparesis: Preliminary Evidence.Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface.Brain-Computer Interface Training after Stroke Affects Patterns of Brain-Behavior Relationships in Corticospinal Motor Fibers.A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke.Role of the Contralesional vs. Ipsilesional Hemisphere in Stroke Recovery.Interaction of BCI with the underlying neurological conditions in patients: pros and cons.Scalp acupuncture plus low-frequency rTMS promotes repair of brain white matter tracts in stroke patients: A DTI study.Machine Learning Classification to Identify the Stage of Brain-Computer Interface Therapy for Stroke Rehabilitation Using Functional Connectivity.Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis.Comparison of Multi-Tensor Diffusion Models' Performance for White Matter Integrity Estimation in Chronic Stroke.Early Findings on Functional Connectivity Correlates of Behavioral Outcomes of Brain-Computer Interface Stroke Rehabilitation Using Machine LearningThe Changing Brain: Bidirectional Learning Between Algorithm and User
P2860
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P2860
Characterizing relationships of DTI, fMRI, and motor recovery in stroke rehabilitation utilizing brain-computer interface technology
description
2014 nî lūn-bûn
@nan
2014 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Characterizing relationships o ...... -computer interface technology
@ast
Characterizing relationships o ...... -computer interface technology
@en
type
label
Characterizing relationships o ...... -computer interface technology
@ast
Characterizing relationships o ...... -computer interface technology
@en
prefLabel
Characterizing relationships o ...... -computer interface technology
@ast
Characterizing relationships o ...... -computer interface technology
@en
P2093
P2860
P356
P1476
Characterizing relationships o ...... -computer interface technology
@en
P2093
Brittany M Young
Dorothy Farrar-Edwards
Justin A Sattin
Justin C Williams
Kristin E Caldera
Leo M Walton
Mitchell E Tyler
Scott W Grogan
Veena A Nair
P2860
P356
10.3389/FNENG.2014.00031
P577
2014-07-29T00:00:00Z