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.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

685 related items for PubMed ID: 18232349

  • 1. Optimized wavelets for blind separation of nonstationary surface myoelectric signals.
    Farina D, Lucas MF, Doncarli C.
    IEEE Trans Biomed Eng; 2008 Jan; 55(1):78-86. PubMed ID: 18232349
    [Abstract] [Full Text] [Related]

  • 2. Blind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals.
    Farina D, Févotte C, Doncarli C, Merletti R.
    IEEE Trans Biomed Eng; 2004 Sep; 51(9):1555-67. PubMed ID: 15376504
    [Abstract] [Full Text] [Related]

  • 3. Entropy-based optimization of wavelet spatial filters.
    Farina D, Kamavuako EN, Wu J, Naddeo F.
    IEEE Trans Biomed Eng; 2008 Mar; 55(3):914-22. PubMed ID: 18334382
    [Abstract] [Full Text] [Related]

  • 4. Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study.
    Karlsson S, Yu J, Akay M.
    IEEE Trans Biomed Eng; 2000 Feb; 47(2):228-38. PubMed ID: 10721630
    [Abstract] [Full Text] [Related]

  • 5. Compression of EMG signals with wavelet transform and artificial neural networks.
    Berger Pde A, Nascimento FA, do Carmo JC, da Rocha AF.
    Physiol Meas; 2006 Jun; 27(6):457-65. PubMed ID: 16603798
    [Abstract] [Full Text] [Related]

  • 6. A fast and reliable technique for muscle activity detection from surface EMG signals.
    Merlo A, Farina D, Merletti R.
    IEEE Trans Biomed Eng; 2003 Mar; 50(3):316-23. PubMed ID: 12669988
    [Abstract] [Full Text] [Related]

  • 7. A bi-dimensional index for the selective assessment of myoelectric manifestations of peripheral and central muscle fatigue.
    Mesin L, Cescon C, Gazzoni M, Merletti R, Rainoldi A.
    J Electromyogr Kinesiol; 2009 Oct; 19(5):851-63. PubMed ID: 18824375
    [Abstract] [Full Text] [Related]

  • 8. A criterion for signal-based selection of wavelets for denoising intrafascicular nerve recordings.
    Kamavuako EN, Jensen W, Yoshida K, Kurstjens M, Farina D.
    J Neurosci Methods; 2010 Feb 15; 186(2):274-80. PubMed ID: 19962403
    [Abstract] [Full Text] [Related]

  • 9. Noise reduction based on ICA decomposition and wavelet transform for the extraction of motor unit action potentials.
    Ren X, Yan Z, Wang Z, Hu X.
    J Neurosci Methods; 2006 Dec 15; 158(2):313-22. PubMed ID: 16831466
    [Abstract] [Full Text] [Related]

  • 10. A new method for the extraction and classification of single motor unit action potentials from surface EMG signals.
    Gazzoni M, Farina D, Merletti R.
    J Neurosci Methods; 2004 Jul 30; 136(2):165-77. PubMed ID: 15183268
    [Abstract] [Full Text] [Related]

  • 11. Surface myoelectric signal analysis: dynamic approaches for change detection and classification.
    Al-Assaf Y.
    IEEE Trans Biomed Eng; 2006 Nov 30; 53(11):2248-56. PubMed ID: 17073330
    [Abstract] [Full Text] [Related]

  • 12. Blind source separation of peripheral nerve recordings.
    Tesfayesus W, Durand DM.
    J Neural Eng; 2007 Sep 30; 4(3):S157-67. PubMed ID: 17873415
    [Abstract] [Full Text] [Related]

  • 13. Robust time delay estimation of bioelectric signals using least absolute deviation neural network.
    Wang Z, He Z, Chen JD.
    IEEE Trans Biomed Eng; 2005 Mar 30; 52(3):454-62. PubMed ID: 15759575
    [Abstract] [Full Text] [Related]

  • 14. Fatigue estimation with a multivariable myoelectric mapping function.
    MacIsaac DT, Parker PA, Englehart KB, Rogers DR.
    IEEE Trans Biomed Eng; 2006 Apr 30; 53(4):694-700. PubMed ID: 16602576
    [Abstract] [Full Text] [Related]

  • 15. Estimation of motor unit conduction velocity from surface EMG recordings by signal-based selection of the spatial filters.
    Mesin L, Tizzani F, Farina D.
    IEEE Trans Biomed Eng; 2006 Oct 30; 53(10):1963-71. PubMed ID: 17019860
    [Abstract] [Full Text] [Related]

  • 16. Compression of multidimensional biomedical signals with spatial and temporal codebook-excited linear prediction.
    Carotti ES, De Martin JC, Merletti R, Farina D.
    IEEE Trans Biomed Eng; 2009 Nov 30; 56(11):2604-10. PubMed ID: 19643696
    [Abstract] [Full Text] [Related]

  • 17. A novel approach for estimating muscle fiber conduction velocity by spatial and temporal filtering of surface EMG signals.
    Farina D, Merletti R.
    IEEE Trans Biomed Eng; 2003 Dec 30; 50(12):1340-51. PubMed ID: 14656063
    [Abstract] [Full Text] [Related]

  • 18. Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms.
    Ozsert M, Yavuz O, Durak-Ata L.
    Comput Methods Biomech Biomed Engin; 2011 Jun 30; 14(6):521-5. PubMed ID: 20645198
    [Abstract] [Full Text] [Related]

  • 19. Estimation of muscle fiber conduction velocity with a spectral multidip approach.
    Farina D, Negro F.
    IEEE Trans Biomed Eng; 2007 Sep 30; 54(9):1583-9. PubMed ID: 17867350
    [Abstract] [Full Text] [Related]

  • 20. Characterization of surface EMG signal based on fuzzy entropy.
    Chen W, Wang Z, Xie H, Yu W.
    IEEE Trans Neural Syst Rehabil Eng; 2007 Jun 30; 15(2):266-72. PubMed ID: 17601197
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 35.