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PUBMED FOR HANDHELDS

Journal Abstract Search


363 related items for PubMed ID: 12611366

  • 1. Classification of finger activation for use in a robotic prosthesis arm.
    Peleg D, Braiman E, Yom-Tov E, Inbar GF.
    IEEE Trans Neural Syst Rehabil Eng; 2002 Dec; 10(4):290-3. PubMed ID: 12611366
    [Abstract] [Full Text] [Related]

  • 2. 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
    [Abstract] [Full Text] [Related]

  • 3. Feature selection for the classification of movements from single movement-related potentials.
    Yom-Tov E, Inbar GF.
    IEEE Trans Neural Syst Rehabil Eng; 2002 Sep; 10(3):170-7. PubMed ID: 12503782
    [Abstract] [Full Text] [Related]

  • 4. Online electromyographic control of a robotic prosthesis.
    Shenoy P, Miller KJ, Crawford B, Rao RN.
    IEEE Trans Biomed Eng; 2008 Mar; 55(3):1128-35. PubMed ID: 18334405
    [Abstract] [Full Text] [Related]

  • 5. Uncovering patterns of forearm muscle activity using multi-channel mechanomyography.
    Alves N, Chau T.
    J Electromyogr Kinesiol; 2010 Oct; 20(5):777-86. PubMed ID: 19854064
    [Abstract] [Full Text] [Related]

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

  • 7. Laboratory evaluation of a unified theory for simultaneous multiple axis artificial arm control.
    Jerard RB, Jacobsen SC.
    J Biomech Eng; 1980 Aug; 102(3):199. PubMed ID: 19530801
    [Abstract] [Full Text] [Related]

  • 8. Dexterous control of a prosthetic hand using fine-wire intramuscular electrodes in targeted extrinsic muscles.
    Cipriani C, Segil JL, Birdwell JA, ff Weir RF.
    IEEE Trans Neural Syst Rehabil Eng; 2014 Jul; 22(4):828-36. PubMed ID: 24760929
    [Abstract] [Full Text] [Related]

  • 9. Correlation analysis of electromyogram signals for multiuser myoelectric interfaces.
    Khushaba RN.
    IEEE Trans Neural Syst Rehabil Eng; 2014 Jul; 22(4):745-55. PubMed ID: 24760933
    [Abstract] [Full Text] [Related]

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  • 11. High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control.
    Daley H, Englehart K, Hargrove L, Kuruganti U.
    J Electromyogr Kinesiol; 2012 Jun; 22(3):478-84. PubMed ID: 22269773
    [Abstract] [Full Text] [Related]

  • 12. Fine detection of grasp force and posture by amputees via surface electromyography.
    Castellini C, Gruppioni E, Davalli A, Sandini G.
    J Physiol Paris; 2009 Jun; 103(3-5):255-62. PubMed ID: 19665563
    [Abstract] [Full Text] [Related]

  • 13. Effects of motor imagery are dependent on motor strategies.
    Liang N, Ni Z, Takahashi M, Murakami T, Yahagi S, Funase K, Kato T, Kasai T.
    Neuroreport; 2007 Aug 06; 18(12):1241-5. PubMed ID: 17632275
    [Abstract] [Full Text] [Related]

  • 14. 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 06; 14(5):539-54. PubMed ID: 15301773
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  • 17. Relation between object properties and EMG during reaching to grasp.
    Fligge N, Urbanek H, van der Smagt P.
    J Electromyogr Kinesiol; 2013 Apr 06; 23(2):402-10. PubMed ID: 23207412
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  • 19. Electromyographic assessment of trunk muscle activation amplitudes during a simulated lifting task using pattern recognition techniques.
    Butler HL, Hubley-Kozey CL, Kozey JW.
    J Electromyogr Kinesiol; 2009 Dec 06; 19(6):e505-12. PubMed ID: 19041264
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