BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

338 related articles for article (PubMed ID: 32714167)

  • 1. Temporal Combination Pattern Optimization Based on Feature Selection Method for Motor Imagery BCIs.
    Jiang J; Wang C; Wu J; Qin W; Xu M; Yin E
    Front Hum Neurosci; 2020; 14():231. PubMed ID: 32714167
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI.
    Zhang Y; Nam CS; Zhou G; Jin J; Wang X; Cichocki A
    IEEE Trans Cybern; 2019 Sep; 49(9):3322-3332. PubMed ID: 29994667
    [TBL] [Abstract][Full Text] [Related]  

  • 3. The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification.
    Zhang S; Zhu Z; Zhang B; Feng B; Yu T; Li Z
    Sensors (Basel); 2020 Aug; 20(17):. PubMed ID: 32842635
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI.
    Kumar S; Mamun K; Sharma A
    Comput Biol Med; 2017 Dec; 91():231-242. PubMed ID: 29100117
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Transformed common spatial pattern for motor imagery-based brain-computer interfaces.
    Ma Z; Wang K; Xu M; Yi W; Xu F; Ming D
    Front Neurosci; 2023; 17():1116721. PubMed ID: 36960172
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Online detection of class-imbalanced error-related potentials evoked by motor imagery.
    Liu Q; Zheng W; Chen K; Ma L; Ai Q
    J Neural Eng; 2021 Apr; 18(4):. PubMed ID: 33823492
    [No Abstract]   [Full Text] [Related]  

  • 7. Correlation-based channel selection and regularized feature optimization for MI-based BCI.
    Jin J; Miao Y; Daly I; Zuo C; Hu D; Cichocki A
    Neural Netw; 2019 Oct; 118():262-270. PubMed ID: 31326660
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Learning Optimal Time-Frequency-Spatial Features by the CiSSA-CSP Method for Motor Imagery EEG Classification.
    Hu H; Pu Z; Li H; Liu Z; Wang P
    Sensors (Basel); 2022 Nov; 22(21):. PubMed ID: 36366225
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved motor imagery classification using adaptive spatial filters based on particle swarm optimization algorithm.
    Xiong X; Wang Y; Song T; Huang J; Kang G
    Front Neurosci; 2023; 17():1303648. PubMed ID: 38192510
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Towards correlation-based time window selection method for motor imagery BCIs.
    Feng J; Yin E; Jin J; Saab R; Daly I; Wang X; Hu D; Cichocki A
    Neural Netw; 2018 Jun; 102():87-95. PubMed ID: 29558654
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The backtracking search optimization algorithm for frequency band and time segment selection in motor imagery-based brain-computer interfaces.
    Wei Z; Wei Q
    J Integr Neurosci; 2016 Sep; 15(3):347-364. PubMed ID: 27681162
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.
    Zhang Y; Zhou G; Jin J; Wang X; Cichocki A
    J Neurosci Methods; 2015 Nov; 255():85-91. PubMed ID: 26277421
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A penalized time-frequency band feature selection and classification procedure for improved motor intention decoding in multichannel EEG.
    Peterson V; Wyser D; Lambercy O; Spies R; Gassert R
    J Neural Eng; 2019 Feb; 16(1):016019. PubMed ID: 30623892
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A spatial-frequency-temporal optimized feature sparse representation-based classification method for motor imagery EEG pattern recognition.
    Miao M; Wang A; Liu F
    Med Biol Eng Comput; 2017 Sep; 55(9):1589-1603. PubMed ID: 28161876
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification.
    Miao Y; Jin J; Daly I; Zuo C; Wang X; Cichocki A; Jung TP
    IEEE Trans Neural Syst Rehabil Eng; 2021; 29():699-707. PubMed ID: 33819158
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals.
    Malan NS; Sharma S
    Comput Biol Med; 2019 Apr; 107():118-126. PubMed ID: 30802693
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Feature optimization based on improved novel global harmony search algorithm for motor imagery electroencephalogram classification.
    Shi B; Chen X; Yue Z; Zeng F; Yin S; Wang B; Wang J
    Front Comput Neurosci; 2022; 16():1004301. PubMed ID: 36589278
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Improvement motor imagery EEG classification based on sparse common spatial pattern and regularized discriminant analysis.
    Fu R; Han M; Tian Y; Shi P
    J Neurosci Methods; 2020 Sep; 343():108833. PubMed ID: 32619588
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi-class EEG classification of motor imagery signal by finding optimal time segments and features using SNR-based mutual information.
    Mahmoudi M; Shamsi M
    Australas Phys Eng Sci Med; 2018 Dec; 41(4):957-972. PubMed ID: 30338495
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.
    Kumar S; Sharma A; Tsunoda T
    BMC Bioinformatics; 2017 Dec; 18(Suppl 16):545. PubMed ID: 29297303
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.