BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

154 related articles for article (PubMed ID: 29547700)

  • 1. A Combined Methodology to Eliminate Artifacts in Multichannel Electrogastrogram Based on Independent Component Analysis and Ensemble Empirical Mode Decomposition.
    Sengottuvel S; Khan PF; Mariyappa N; Patel R; Saipriya S; Gireesan K
    SLAS Technol; 2018 Jun; 23(3):269-280. PubMed ID: 29547700
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Artifact reduction in electrogastrogram based on empirical mode decomposition method.
    Liang H; Lin Z; McCallum RW
    Med Biol Eng Comput; 2000 Jan; 38(1):35-41. PubMed ID: 10829388
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Novel Method Based on Combination of Independent Component Analysis and Ensemble Empirical Mode Decomposition for Removing Electrooculogram Artifacts From Multichannel Electroencephalogram Signals.
    Teng CL; Zhang YY; Wang W; Luo YY; Wang G; Xu J
    Front Neurosci; 2021; 15():729403. PubMed ID: 34707475
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Baseline drift removal and denoising of MCG data using EEMD: role of noise amplitude and the thresholding effect.
    Mariyappa N; Sengottuvel S; Parasakthi C; Gireesan K; Janawadkar MP; Radhakrishnan TS; Sundar CS
    Med Eng Phys; 2014 Oct; 36(10):1266-76. PubMed ID: 25074650
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Arrhythmia ECG noise reduction by ensemble empirical mode decomposition.
    Chang KM
    Sensors (Basel); 2010; 10(6):6063-80. PubMed ID: 22219702
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A modified algorithm of the combined ensemble empirical mode decomposition and independent component analysis for the removal of cardiac artifacts from neuromuscular electrical signals.
    Lee KJ; Choi EK; Lee SM; Oh S; Lee B
    Physiol Meas; 2014 Apr; 35(4):657-75. PubMed ID: 24622011
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automatic selection of IMFs to denoise the sEMG signals using EMD.
    Koppolu PK; Chemmangat K
    J Electromyogr Kinesiol; 2023 Dec; 73():102834. PubMed ID: 37922679
    [TBL] [Abstract][Full Text] [Related]  

  • 8. EEMD and Multiscale PCA-Based Signal Denoising Method and Its Application to Seismic P-Phase Arrival Picking.
    Peng K; Guo H; Shang X
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450710
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Extraction of gastric slow waves from electrogastrograms: combining independent component analysis and adaptive signal enhancement.
    Liang H
    Med Biol Eng Comput; 2005 Mar; 43(2):245-51. PubMed ID: 15865135
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique.
    Sweeney KT; McLoone SF; Ward TE
    IEEE Trans Biomed Eng; 2013 Jan; 60(1):97-105. PubMed ID: 23086501
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Sensitivity enhancement of task-evoked fMRI using ensemble empirical mode decomposition.
    Lin SH; Lin GH; Tsai PJ; Hsu AL; Lo MT; Yang AC; Lin CP; Wu CW
    J Neurosci Methods; 2016 Jan; 258():56-66. PubMed ID: 26523767
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Removal of artifacts in knee joint vibroarthrographic signals using ensemble empirical mode decomposition and detrended fluctuation analysis.
    Wu Y; Yang S; Zheng F; Cai S; Lu M; Wu M
    Physiol Meas; 2014 Mar; 35(3):429-39. PubMed ID: 24521557
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessment of slow wave propagation in multichannel electrogastrography by using noise-assisted multivariate empirical mode decomposition and cross-covariance analysis.
    Mika B; Komorowski D; Tkacz E
    Comput Biol Med; 2018 Sep; 100():305-315. PubMed ID: 29397919
    [TBL] [Abstract][Full Text] [Related]  

  • 14. SVR-EEMD: An Improved EEMD Method Based on Support Vector Regression Extension in PPG Signal Denoising.
    Liu G; Hu X; Wang E; Zhou G; Cai J; Zhang S
    Comput Math Methods Med; 2019; 2019():5363712. PubMed ID: 31915461
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Eye blink artifact rejection in single-channel electroencephalographic signals by complete ensemble empirical mode decomposition and independent component analysis.
    Kanoga S; Mitsukura Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():121-4. PubMed ID: 26736215
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Ensemble Empirical Mode Decomposition based methodology for ultrasonic testing of coarse grain austenitic stainless steels.
    Sharma GK; Kumar A; Jayakumar T; Purnachandra Rao B; Mariyappa N
    Ultrasonics; 2015 Mar; 57():167-78. PubMed ID: 25488024
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Analysis of laser speckle contrast images variability using a novel empirical mode decomposition: comparison of results with laser Doppler flowmetry signals variability.
    Humeau-Heurtier A; Abraham P; Mahe G
    IEEE Trans Med Imaging; 2015 Feb; 34(2):618-27. PubMed ID: 25347875
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An EEMD-ICA Approach to Enhancing Artifact Rejection for Noisy Multivariate Neural Data.
    Zeng K; Chen D; Ouyang G; Wang L; Liu X; Li X
    IEEE Trans Neural Syst Rehabil Eng; 2016 Jun; 24(6):630-8. PubMed ID: 26552089
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Fast Approach to Removing Muscle Artifacts for EEG with Signal Serialization Based Ensemble Empirical Mode Decomposition.
    Dai Y; Duan F; Feng F; Sun Z; Zhang Y; Caiafa CF; Marti-Puig P; Solé-Casals J
    Entropy (Basel); 2021 Sep; 23(9):. PubMed ID: 34573795
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.