These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

148 related articles for article (PubMed ID: 24550696)

  • 1. Removal of EOG artifacts from EEG recordings using stationary subspace analysis.
    Zeng H; Song A
    ScientificWorldJournal; 2014; 2014():259121. PubMed ID: 24550696
    [TBL] [Abstract][Full Text] [Related]  

  • 2. EOG artifact correction from EEG recording using stationary subspace analysis and empirical mode decomposition.
    Zeng H; Song A; Yan R; Qin H
    Sensors (Basel); 2013 Nov; 13(11):14839-59. PubMed ID: 24189330
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Hybrid algorithm for multi artifact removal from single channel EEG.
    Noorbasha SK; Florence Sudha G
    Biomed Phys Eng Express; 2021 May; 7(4):. PubMed ID: 33930879
    [TBL] [Abstract][Full Text] [Related]  

  • 4. SNOAR: a new regression approach for the removal of ocular artifact from multi-channel electroencephalogram signals.
    Juyal R; Muthusamy H; Kumar N
    Med Biol Eng Comput; 2022 Dec; 60(12):3567-3583. PubMed ID: 36245020
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An iterative subspace denoising algorithm for removing electroencephalogram ocular artifacts.
    Sameni R; Gouy-Pailler C
    J Neurosci Methods; 2014 Mar; 225():97-105. PubMed ID: 24486874
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements.
    Kilicarslan A; Grossman RG; Contreras-Vidal JL
    J Neural Eng; 2016 Apr; 13(2):026013. PubMed ID: 26863159
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Removing electroencephalographic artifacts by blind source separation.
    Jung TP; Makeig S; Humphries C; Lee TW; McKeown MJ; Iragui V; Sejnowski TJ
    Psychophysiology; 2000 Mar; 37(2):163-78. PubMed ID: 10731767
    [TBL] [Abstract][Full Text] [Related]  

  • 8. High-throughput ocular artifact reduction in multichannel electroencephalography (EEG) using component subspace projection.
    Ma J; Bayram S; Tao P; Svetnik V
    J Neurosci Methods; 2011 Mar; 196(1):131-40. PubMed ID: 21236300
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Research on removal algorithm of EOG artifacts in single-channel EEG signals based on CEEMDAN-BD.
    Wu Q; Zhang W; Wang Y; Zhang W; Liu X
    Comput Methods Biomech Biomed Engin; 2021 Sep; 24(12):1368-1379. PubMed ID: 33620279
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: a simulation case.
    Romero S; Mañanas MA; Barbanoj MJ
    Comput Biol Med; 2008 Mar; 38(3):348-60. PubMed ID: 18222418
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automated CCA-MWF Algorithm for Unsupervised Identification and Removal of EOG Artifacts From EEG.
    Miao M; Hu W; Xu B; Zhang J; Rodrigues JJPC; de Albuquerque VHC
    IEEE J Biomed Health Inform; 2022 Aug; 26(8):3607-3617. PubMed ID: 34847047
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic removal of eye movement and blink artifacts from EEG data using blind component separation.
    Joyce CA; Gorodnitsky IF; Kutas M
    Psychophysiology; 2004 Mar; 41(2):313-25. PubMed ID: 15032997
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.
    Zou Y; Nathan V; Jafari R
    IEEE J Biomed Health Inform; 2016 Jan; 20(1):73-81. PubMed ID: 25415992
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The removal of ocular artifacts from EEG signals using adaptive filters based on ocular source components.
    Chan HL; Tsai YT; Meng LF; Wu T
    Ann Biomed Eng; 2010 Nov; 38(11):3489-99. PubMed ID: 20532631
    [TBL] [Abstract][Full Text] [Related]  

  • 15. EEGANet: Removal of Ocular Artifacts From the EEG Signal Using Generative Adversarial Networks.
    Sawangjai P; Trakulruangroj M; Boonnag C; Piriyajitakonkij M; Tripathy RK; Sudhawiyangkul T; Wilaiprasitporn T
    IEEE J Biomed Health Inform; 2022 Oct; 26(10):4913-4924. PubMed ID: 34826300
    [TBL] [Abstract][Full Text] [Related]  

  • 16. SSA with CWT and
    Maddirala AK; Veluvolu KC
    Sensors (Basel); 2022 Jan; 22(3):. PubMed ID: 35161676
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis.
    Liu Q; Liu A; Zhang X; Chen X; Qian R; Chen X
    J Healthc Eng; 2019; 2019():4159676. PubMed ID: 31976053
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.
    Wang G; Teng C; Li K; Zhang Z; Yan X
    IEEE J Biomed Health Inform; 2016 Sep; 20(5):1301-8. PubMed ID: 26126290
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Online Recursive ICA Algorithm Used for Motor Imagery EEG Signal.
    Lin X; Wang L; Ohtsuki T
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():502-505. PubMed ID: 33018037
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Automatic removal algorithm of electrooculographic artifacts in non-invasive brain-computer interface based on independent component analysis].
    Song H; Xu S; Liu G; Liu J; Xiong P
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2022 Dec; 39(6):1074-1081. PubMed ID: 36575075
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.