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 *

120 related articles for article (PubMed ID: 11850043)

  • 41. The application of independent component analysis to the multi-channel surface electromyographic signals for separation of motor unit action potential trains: part I-measuring techniques.
    Nakamura H; Yoshida M; Kotani M; Akazawa K; Moritani T
    J Electromyogr Kinesiol; 2004 Aug; 14(4):423-32. PubMed ID: 15165592
    [TBL] [Abstract][Full Text] [Related]  

  • 42. The influence of contraction amplitude and firing history on spike-triggered averaged trapezius motor unit potentials.
    Westad C; Westgaard RH
    J Physiol; 2005 Feb; 562(Pt 3):965-75. PubMed ID: 15576452
    [TBL] [Abstract][Full Text] [Related]  

  • 43. A two-stage method for MUAP classification based on EMG decomposition.
    Katsis CD; Exarchos TP; Papaloukas C; Goletsis Y; Fotiadis DI; Sarmas I
    Comput Biol Med; 2007 Sep; 37(9):1232-40. PubMed ID: 17208215
    [TBL] [Abstract][Full Text] [Related]  

  • 44. [Research on the surface electromyography signal decomposition based on multi-channel signal fusion analysis].
    Li Q; Yang J
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2012 Oct; 29(5):948-53. PubMed ID: 23198440
    [TBL] [Abstract][Full Text] [Related]  

  • 45. A new and fast approach towards sEMG decomposition.
    Gligorijević I; van Dijk JP; Mijović B; Van Huffel S; Blok JH; De Vos M
    Med Biol Eng Comput; 2013 May; 51(5):593-605. PubMed ID: 23329211
    [TBL] [Abstract][Full Text] [Related]  

  • 46. The application of independent component analysis to the multi-channel surface electromyographic signals for separation of motor unit action potential trains: part II-modelling interpretation.
    Nakamura H; Yoshida M; Kotani M; Akazawa K; Moritani T
    J Electromyogr Kinesiol; 2004 Aug; 14(4):433-41. PubMed ID: 15165593
    [TBL] [Abstract][Full Text] [Related]  

  • 47. 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]  

  • 48. Using two-dimensional spatial information in decomposition of surface EMG signals.
    Kleine BU; van Dijk JP; Lapatki BG; Zwarts MJ; Stegeman DF
    J Electromyogr Kinesiol; 2007 Oct; 17(5):535-48. PubMed ID: 16904342
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Coherence and short-term synchronization are insensitive to motor unit spike train nonstationarity.
    Terry K; Griffin L
    J Neurosci Methods; 2010 Jan; 185(2):185-98. PubMed ID: 19698748
    [TBL] [Abstract][Full Text] [Related]  

  • 50. [Computer-assisted analysis of the electromyogram for routine clinical use].
    Strempel JF; Feistner H; Münte TF; Hinrichs H; Heinze HJ
    EEG EMG Z Elektroenzephalogr Elektromyogr Verwandte Geb; 1992 Sep; 23(3):127-34. PubMed ID: 1425388
    [TBL] [Abstract][Full Text] [Related]  

  • 51. 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; 136(2):165-77. PubMed ID: 15183268
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Automatic identification of motor unit action potential trains from electromyographic signals using fuzzy techniques.
    Chauvet E; Fokapu O; Hogrel JY; Gamet D; Duchêne J
    Med Biol Eng Comput; 2003 Nov; 41(6):646-53. PubMed ID: 14686590
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Motor unit recruitment and rate coding in response to fatiguing shoulder abductions and subsequent recovery.
    Jensen BR; Pilegaard M; Sjøgaard G
    Eur J Appl Physiol; 2000 Oct; 83(2-3):190-9. PubMed ID: 11104060
    [TBL] [Abstract][Full Text] [Related]  

  • 54. SVM-based validation of motor unit potential trains extracted by EMG signal decomposition.
    Parsaei H; Stashuk DW
    IEEE Trans Biomed Eng; 2012 Jan; 59(1):183-91. PubMed ID: 21954194
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Efficient parameterization of MUAP signal for identification of MU and volume conductor characteristics using neural networks.
    Reffad A; Bekka RE; Mebarkia K; Chikouche D
    J Neurosci Methods; 2007 Aug; 164(2):325-38. PubMed ID: 17544153
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Feature selection for motor unit potential train characterization.
    Abdelmaseeh M; Smith B; Stashuk D
    Muscle Nerve; 2014 May; 49(5):680-90. PubMed ID: 23893614
    [TBL] [Abstract][Full Text] [Related]  

  • 57. 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]  

  • 58. Motor unit properties after operant conditioning of rat H-reflex.
    Carp JS; Chen XY; Sheikh H; Wolpaw JR
    Exp Brain Res; 2001 Oct; 140(3):382-6. PubMed ID: 11681314
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Decomposition of surface EMG signals.
    De Luca CJ; Adam A; Wotiz R; Gilmore LD; Nawab SH
    J Neurophysiol; 2006 Sep; 96(3):1646-57. PubMed ID: 16899649
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Skill and selection bias has least influence on motor unit action potential firing rate/frequency.
    Chu J; Takehara I; Li TC; Schwartz I
    Electromyogr Clin Neurophysiol; 2003; 43(7):387-92. PubMed ID: 14626717
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.