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Standards
| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
|---|---|---|---|
| 1 |
Material Type: Standards
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A Transferable Deep Learning Prognosis Model for Predicting Stroke Patients' Recovery in Different Rehabilitation TrainingsBiomedical and Health Informatics, IEEE Journal of, 2022, Vol.26, p.6003-60112013 IEEE ;DOI: 10.1109/JBHI.2022.3205436Full text available |
| 2 |
Material Type: Standards
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Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content AnalysisNeural Systems and Rehabilitation Engineering, IEEE Transactions on, 2023, Vol.31, p.3341-33522001-2011 IEEE ;DOI: 10.1109/TNSRE.2023.3304758Full text available |
| 3 |
Material Type: Standards
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Applying Action Observation During a Brain-Computer Interface on Upper Limb Recovery in Chronic Stroke PatientsAccess, IEEE, 2023, Vol.11, p.4931-49432013 IEEE ;DOI: 10.1109/ACCESS.2023.3236182Full text available |
| 4 |
Material Type: Standards
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Driving-PASS: A Driving Performance Assessment System for Stroke Drivers Using Deep FeaturesAccess, IEEE, 2021, Vol.9, p.21627-216412013 IEEE ;DOI: 10.1109/ACCESS.2021.3055870Full text available |
| 5 |
Material Type: Standards
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Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury ClassificationBiomedical Engineering, IEEE Transactions on, 2021, Vol.68, p.3205-32161964-2012 IEEE ;DOI: 10.1109/TBME.2021.3062502Full text available |
| 6 |
Material Type: Standards
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Motor Imagery and Action Observation Induced Electroencephalographic Activations to Guide Subject-Specific Training Paradigm: A Pilot StudyNeural Systems and Rehabilitation Engineering, IEEE Transactions on, 2023, Vol.31, p.2457-24672001-2011 IEEE ;DOI: 10.1109/TNSRE.2023.3275572Full text available |
| 7 |
Material Type: Standards
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Characterization of Multilayer Piezoelectric Stacks Down to 100KUltrasonics, Ferroelectrics, and Frequency Control, IEEE Open Journal of, 2022, Vol.2, p.65-822021 IEEE ;DOI: 10.1109/OJUFFC.2022.3173919Full text available |
| 8 |
Material Type: Standards
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Decoding Multi-Class EEG Signals of Hand Movement Using Multivariate Empirical Mode Decomposition and Convolutional Neural NetworkNeural Systems and Rehabilitation Engineering, IEEE Transactions on, 2022, Vol.30, p.2754-27632001-2011 IEEE ;DOI: 10.1109/TNSRE.2022.3208710Full text available |
| 9 |
Material Type: Standards
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SketchSegNet+: An End-to-End Learning of RNN for Multi-Class Sketch Semantic SegmentationAccess, IEEE, 2019, Vol.7, p.102717-1027262013 IEEE ;DOI: 10.1109/ACCESS.2019.2929804Full text available |
| 10 |
Material Type: Standards
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Automated FES for Upper Limb Rehabilitation Following Stroke and Spinal Cord InjuryNeural Systems and Rehabilitation Engineering, IEEE Transactions on, 2018, Vol.26, p.1067-10742001-2011 IEEE ;DOI: 10.1109/TNSRE.2018.2816238Full text available |
| 11 |
Material Type: Standards
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Studying Direct Lightning Stroke Impact on Human Safety Near HVTL Towers Considering Two Layer Soils and Ionization InfluenceAccess, IEEE, 2023, Vol.11, p.5019-50302013 IEEE ;DOI: 10.1109/ACCESS.2023.3235874Full text available |
| 12 |
Material Type: Standards
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A Coverless Plain Text Steganography Based on Character FeaturesAccess, IEEE, 2019, Vol.7, p.95665-956762013 IEEE ;DOI: 10.1109/ACCESS.2019.2929123Full text available |
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Subject
- Stroke (9)
- Electroencephalography (5)
- Task Analysis (4)
- Training (3)
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- Semantics (2)
- Motor Imagery (2)
- Robot Sensing Systems (2)
- Patient Rehabilitation (2)
- Action Observation (2)
- Electrodes (2)
- Brain-Computer Interface (1)
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- Brain Injuries (1)
- Analytical Models (1)
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