BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

273 related articles for article (PubMed ID: 18617420)

  • 1. Fractal analysis of surface electromyography signals: a novel power spectrum-based method.
    Talebinejad M; Chan AD; Miri A; Dansereau RM
    J Electromyogr Kinesiol; 2009 Oct; 19(5):840-50. PubMed ID: 18617420
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fatigue estimation using a novel multi-fractal detrended fluctuation analysis-based approach.
    Talebinejad M; Chan AD; Miri A
    J Electromyogr Kinesiol; 2010 Jun; 20(3):433-9. PubMed ID: 19589697
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Classification of surface EMG signal with fractal dimension.
    Hu X; Wang ZZ; Ren XM
    J Zhejiang Univ Sci B; 2005 Aug; 6(8):844-8. PubMed ID: 16052721
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Surface myoelectric signal classification for prostheses control.
    Al-Assaf Y; Al-Nashash H
    J Med Eng Technol; 2005; 29(5):203-7. PubMed ID: 16126579
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Influence of high motor unit synchronization levels on non-linear and spectral variables of the surface EMG.
    Fattorini L; Felici F; Filligoi GC; Traballesi M; Farina D
    J Neurosci Methods; 2005 Apr; 143(2):133-9. PubMed ID: 15814145
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Can standard surface EMG processing parameters be used to estimate motor unit global firing rate?
    Zhou P; Rymer WZ
    J Neural Eng; 2004 Jun; 1(2):99-110. PubMed ID: 15876628
    [TBL] [Abstract][Full Text] [Related]  

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

  • 11. A Lempel-Ziv complexity measure for muscle fatigue estimation.
    Talebinejad M; Chan AD; Miri A
    J Electromyogr Kinesiol; 2011 Apr; 21(2):236-41. PubMed ID: 21216619
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Vision-based segmentation of continuous mechanomyographic grasping sequences.
    Alves N; Chau T
    IEEE Trans Biomed Eng; 2008 Feb; 55(2 Pt 1):765-73. PubMed ID: 18270015
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Decomposition of intramuscular EMG signals using a heuristic fuzzy expert system.
    Erim Z; Lin W
    IEEE Trans Biomed Eng; 2008 Sep; 55(9):2180-9. PubMed ID: 18713687
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Investigation of optimum electrode locations by using an automatized surface electromyography analysis technique.
    Nishihara K; Kawai H; Gomi T; Terajima M; Chiba Y
    IEEE Trans Biomed Eng; 2008 Feb; 55(2 Pt 1):636-42. PubMed ID: 18269999
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Principal components analysis preprocessing for improved classification accuracies in pattern-recognition-based myoelectric control.
    Hargrove LJ; Li G; Englehart KB; Hudgins BS
    IEEE Trans Biomed Eng; 2009 May; 56(5):1407-14. PubMed ID: 19473932
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A pattern recognition technique to characterize the differential modulation of co-activating muscles at the performer/environment interface.
    Pelland L; McKinley P
    J Electromyogr Kinesiol; 2004 Oct; 14(5):539-54. PubMed ID: 15301773
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automatic segmentation of surface EMG images: Improving the estimation of neuromuscular activity.
    Vieira TM; Merletti R; Mesin L
    J Biomech; 2010 Aug; 43(11):2149-58. PubMed ID: 20444452
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.