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 *

283 related articles for article (PubMed ID: 18619856)

  • 1. Spectrum of the nonstationary electromyographic signal modelled with integral pulse frequency modulation and its application to estimating neural drive information.
    Jiang N; Parker PA; Englehart KB
    J Electromyogr Kinesiol; 2009 Aug; 19(4):e267-79. PubMed ID: 18619856
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Interpretation of EMG integral or RMS and estimates of "neuromuscular efficiency" can be misleading in fatiguing contraction.
    Arabadzhiev TI; Dimitrov VG; Dimitrova NA; Dimitrov GV
    J Electromyogr Kinesiol; 2010 Apr; 20(2):223-32. PubMed ID: 19233687
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The image of motor units architecture in the mechanomyographic signal during the single motor unit contraction: in vivo and simulation study.
    Kaczmarek P; Celichowski J; Drzymała-Celichowska H; Kasiński A
    J Electromyogr Kinesiol; 2009 Aug; 19(4):553-63. PubMed ID: 18455438
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Estimating motor unit discharge patterns from high-density surface electromyogram.
    Holobar A; Farina D; Gazzoni M; Merletti R; Zazula D
    Clin Neurophysiol; 2009 Mar; 120(3):551-62. PubMed ID: 19208498
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modeling of muscle motor unit innervation process correlation and common drive.
    Jiang N; Parker PA; Englehart KB
    IEEE Trans Biomed Eng; 2006 Aug; 53(8):1605-14. PubMed ID: 16916095
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Toward the development of predictive equations of back muscle capacity based on frequency- and temporal-domain electromyographic indices computed from intermittent static contractions.
    Larivière C; Gravel D; Gagnon D; Arsenault AB
    Spine J; 2009; 9(1):87-95. PubMed ID: 18082457
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Power spectrum of the rectified EMG: when and why is rectification beneficial for identifying neural connectivity?
    Negro F; Keenan K; Farina D
    J Neural Eng; 2015 Jun; 12(3):036008. PubMed ID: 25915007
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Extracting simultaneous and proportional neural control information for multiple-DOF prostheses from the surface electromyographic signal.
    Jiang N; Englehart KB; Parker PA
    IEEE Trans Biomed Eng; 2009 Apr; 56(4):1070-80. PubMed ID: 19272889
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Effects of the physiological parameters on the signal-to-noise ratio of single myoelectric channel.
    Ma HT; Zhang YT
    J Neuroeng Rehabil; 2007 Aug; 4():29. PubMed ID: 17686160
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Insight into the motor unit activation and structure properties gained from EMG signal analysis.
    Zalewska E
    Clin Neurophysiol; 2009 Mar; 120(3):449-50. PubMed ID: 19243991
    [No Abstract]   [Full Text] [Related]  

  • 13. 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; 53(10):1963-71. PubMed ID: 17019860
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Simulation analysis of interference EMG during fatiguing voluntary contractions. Part II--changes in amplitude and spectral characteristics.
    Dimitrov GV; Arabadzhiev TI; Hogrel JY; Dimitrova NA
    J Electromyogr Kinesiol; 2008 Feb; 18(1):35-43. PubMed ID: 16963280
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Characteristics of power spectrum density function of EMG during muscle contraction below 30%MVC.
    Roman-Liu D; Konarska M
    J Electromyogr Kinesiol; 2009 Oct; 19(5):864-74. PubMed ID: 18590966
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The synthesis of EMG signals based on considerations of signal spectra.
    Gammans P; Qin SF; Wright DK
    Biomed Sci Instrum; 2003; 39():187-92. PubMed ID: 12724892
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Decoding the neural drive to muscles from the surface electromyogram.
    Farina D; Holobar A; Merletti R; Enoka RM
    Clin Neurophysiol; 2010 Oct; 121(10):1616-23. PubMed ID: 20444646
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Recognition of the physiological actions of the triphasic EMG pattern by a dynamic recurrent neural network.
    Cheron G; Cebolla AM; Bengoetxea A; Leurs F; Dan B
    Neurosci Lett; 2007 Mar; 414(2):192-6. PubMed ID: 17224236
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multiple site electromyograph amplitude estimation.
    Clancy EA; Hogan N
    IEEE Trans Biomed Eng; 1995 Feb; 42(2):203-11. PubMed ID: 7868148
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An examination of the Runs Test, Reverse Arrangements Test, and modified Reverse Arrangements Test for assessing surface EMG signal stationarity.
    Beck TW; Housh TJ; Weir JP; Cramer JT; Vardaxis V; Johnson GO; Coburn JW; Malek MH; Mielke M
    J Neurosci Methods; 2006 Sep; 156(1-2):242-8. PubMed ID: 16621017
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.