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 *

170 related articles for article (PubMed ID: 20639182)

  • 1. Rigorous a posteriori assessment of accuracy in EMG decomposition.
    McGill KC; Marateb HR
    IEEE Trans Neural Syst Rehabil Eng; 2011 Feb; 19(1):54-63. PubMed ID: 20639182
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MUAP number estimates in surface EMG: template-matching methods and their performance boundaries.
    Zhou P; Rymer WZ
    Ann Biomed Eng; 2004 Jul; 32(7):1007-15. PubMed ID: 15298438
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A novel method for automated EMG decomposition and MUAP classification.
    Katsis CD; Goletsis Y; Likas A; Fotiadis DI; Sarmas I
    Artif Intell Med; 2006 May; 37(1):55-64. PubMed ID: 16377160
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application of higher order statistics techniques to EMG signals to characterize the motor unit action potential.
    Shahid S; Walker J; Lyons GM; Byrne CA; Nene AV
    IEEE Trans Biomed Eng; 2005 Jul; 52(7):1195-209. PubMed ID: 16041983
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic decomposition of multichannel intramuscular EMG signals.
    Florestal JR; Mathieu PA; McGill KC
    J Electromyogr Kinesiol; 2009 Feb; 19(1):1-9. PubMed ID: 17513128
    [TBL] [Abstract][Full Text] [Related]  

  • 6. An evaluation of the utility and limitations of counting motor unit action potentials in the surface electromyogram.
    Zhou P; Rymer WZ
    J Neural Eng; 2004 Dec; 1(4):238-45. PubMed ID: 15876644
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Accuracy assessment of CKC high-density surface EMG decomposition in biceps femoris muscle.
    Marateb HR; McGill KC; Holobar A; Lateva ZC; Mansourian M; Merletti R
    J Neural Eng; 2011 Dec; 8(6):066002. PubMed ID: 21975280
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Robust decomposition of single-channel intramuscular EMG signals at low force levels.
    Marateb HR; Muceli S; McGill KC; Merletti R; Farina D
    J Neural Eng; 2011 Dec; 8(6):066015. PubMed ID: 22063475
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automated decomposition of intramuscular electromyographic signals.
    Florestal JR; Mathieu PA; Malanda A
    IEEE Trans Biomed Eng; 2006 May; 53(5):832-9. PubMed ID: 16686405
    [TBL] [Abstract][Full Text] [Related]  

  • 10. EMG signal decomposition using motor unit potential train validity.
    Parsaei H; Stashuk DW
    IEEE Trans Neural Syst Rehabil Eng; 2013 Mar; 21(2):265-74. PubMed ID: 23033332
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Assessment of validity of a high-yield surface electromyogram decomposition.
    Hu X; Rymer WZ; Suresh NL
    J Neuroeng Rehabil; 2013 Sep; 10():99. PubMed ID: 24059856
    [TBL] [Abstract][Full Text] [Related]  

  • 12. New signal processing techniques for the decomposition of EMG signals.
    Loudon GH; Jones NB; Sehmi AS
    Med Biol Eng Comput; 1992 Nov; 30(6):591-9. PubMed ID: 1297013
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients.
    Zennaro D; Wellig P; Koch VM; Moschytz GS; Läubli T
    IEEE Trans Biomed Eng; 2003 Jan; 50(1):58-69. PubMed ID: 12617525
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Improved online decomposition of non-stationary electromyogram via signal enhancement using a neuron resonance model: a simulation study.
    Zheng Y; Xu G; Li Y; Qiang W
    J Neural Eng; 2022 Apr; 19(2):. PubMed ID: 35303735
    [No Abstract]   [Full Text] [Related]  

  • 15. A Multi-Classifier Approach to MUAP Classification for Diagnosis of Neuromuscular Disorders.
    Kamali T; Boostani R; Parsaei H
    IEEE Trans Neural Syst Rehabil Eng; 2014 Jan; 22(1):191-200. PubMed ID: 24263096
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multi-receiver precision decomposition of intramuscular EMG signals.
    Nawab SH; Wotiz RP; De Luca CJ
    Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():1252-5. PubMed ID: 17945629
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Classification of Action Potentials With High Variability Using Convolutional Neural Network for Motor Unit Tracking.
    Li Y; Zheng Y; Xu G; Zhang S; Liang R; Ji R
    IEEE Trans Neural Syst Rehabil Eng; 2024; 32():905-914. PubMed ID: 38335077
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A comparison of three quantitative motor unit analysis algorithms.
    McGill KC
    Suppl Clin Neurophysiol; 2009; 60():273-8. PubMed ID: 20715389
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A simulation study on the relation between the motor unit depth and action potential from multi-channel surface electromyography recordings.
    He J; Luo Z
    J Clin Neurosci; 2018 Aug; 54():146-151. PubMed ID: 29805080
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Study on the classification of motor unit action potentials from single-channel surface EMG signal based on the wavelet analysis].
    Li Q; Yang J
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2010 Aug; 27(4):893-7. PubMed ID: 20842866
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.