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Journal Abstract Search

227 related items for PubMed ID: 16765965

  • 1. Effects of EMG processing on biomechanical models of muscle joint systems: sensitivity of trunk muscle moments, spinal forces, and stability.
    Staudenmann D, Potvin JR, Kingma I, Stegeman DF, van Dieën JH.
    J Biomech; 2007; 40(4):900-9. PubMed ID: 16765965
    [Abstract] [Full Text] [Related]

  • 2. Comparison of trunk muscle forces and spinal loads estimated by two biomechanical models.
    Arjmand N, Gagnon D, Plamondon A, Shirazi-Adl A, Larivière C.
    Clin Biomech (Bristol); 2009 Aug; 24(7):533-41. PubMed ID: 19493597
    [Abstract] [Full Text] [Related]

  • 3. Less is more: high pass filtering, to remove up to 99% of the surface EMG signal power, improves EMG-based biceps brachii muscle force estimates.
    Potvin JR, Brown SH.
    J Electromyogr Kinesiol; 2004 Jun; 14(3):389-99. PubMed ID: 15094152
    [Abstract] [Full Text] [Related]

  • 4. High-pass filtering surface EMG in an attempt to better represent the signals detected at the intramuscular level.
    Brown SH, Brookham RL, Dickerson CR.
    Muscle Nerve; 2010 Feb; 41(2):234-9. PubMed ID: 19722252
    [Abstract] [Full Text] [Related]

  • 5. Trunk muscle activation and associated lumbar spine joint shear forces under different levels of external forward force applied to the trunk.
    Kingma I, Staudenmann D, van Dieën JH.
    J Electromyogr Kinesiol; 2007 Feb; 17(1):14-24. PubMed ID: 16531071
    [Abstract] [Full Text] [Related]

  • 6. Methodological aspects of SEMG recordings for force estimation--a tutorial and review.
    Staudenmann D, Roeleveld K, Stegeman DF, van Dieën JH.
    J Electromyogr Kinesiol; 2010 Jun; 20(3):375-87. PubMed ID: 19758823
    [Abstract] [Full Text] [Related]

  • 7. An EMG-to-force processing approach for determining ankle muscle forces during normal human gait.
    Bogey RA, Perry J, Gitter AJ.
    IEEE Trans Neural Syst Rehabil Eng; 2005 Sep; 13(3):302-10. PubMed ID: 16200754
    [Abstract] [Full Text] [Related]

  • 8. Co-activation alters the linear versus non-linear impression of the EMG-torque relationship of trunk muscles.
    Brown SH, McGill SM.
    J Biomech; 2008 Sep; 41(3):491-7. PubMed ID: 18054943
    [Abstract] [Full Text] [Related]

  • 9. Adaptive whitening in electromyogram amplitude estimation for epoch-based applications.
    Prakash P, Salini CA, Tranquilli JA, Brown DR, Clancy EA.
    IEEE Trans Biomed Eng; 2005 Feb; 52(2):331-4. PubMed ID: 15709671
    [Abstract] [Full Text] [Related]

  • 10. Static optimization of muscle forces during gait in comparison to EMG-to-force processing approach.
    Heintz S, Gutierrez-Farewik EM.
    Gait Posture; 2007 Jul; 26(2):279-88. PubMed ID: 17071088
    [Abstract] [Full Text] [Related]

  • 11. An improved multi-joint EMG-assisted optimization approach to estimate joint and muscle forces in a musculoskeletal model of the lumbar spine.
    Gagnon D, Arjmand N, Plamondon A, Shirazi-Adl A, Larivière C.
    J Biomech; 2011 May 17; 44(8):1521-9. PubMed ID: 21439569
    [Abstract] [Full Text] [Related]

  • 12. Feasibility of using EMG driven neuromusculoskeletal model for prediction of dynamic movement of the elbow.
    Koo TK, Mak AF.
    J Electromyogr Kinesiol; 2005 Feb 17; 15(1):12-26. PubMed ID: 15642650
    [Abstract] [Full Text] [Related]

  • 13. Accuracy of a practicable EMG to force model for knee muscles.
    Doorenbosch CA, Harlaar J.
    Neurosci Lett; 2004 Sep 16; 368(1):78-81. PubMed ID: 15342138
    [Abstract] [Full Text] [Related]

  • 14. A two-step EMG-and-optimization process to estimate muscle force during dynamic movement.
    Amarantini D, Rao G, Berton E.
    J Biomech; 2010 Jun 18; 43(9):1827-30. PubMed ID: 20206935
    [Abstract] [Full Text] [Related]

  • 15. Can standard surface EMG processing parameters be used to estimate motor unit global firing rate?
    Zhou P, Rymer WZ.
    J Neural Eng; 2004 Jun 18; 1(2):99-110. PubMed ID: 15876628
    [Abstract] [Full Text] [Related]

  • 16. A method to combine numerical optimization and EMG data for the estimation of joint moments under dynamic conditions.
    Amarantini D, Martin L.
    J Biomech; 2004 Sep 18; 37(9):1393-404. PubMed ID: 15275847
    [Abstract] [Full Text] [Related]

  • 17. Prediction of joint moments using a neural network model of muscle activations from EMG signals.
    Wang L, Buchanan TS.
    IEEE Trans Neural Syst Rehabil Eng; 2002 Mar 18; 10(1):30-7. PubMed ID: 12173737
    [Abstract] [Full Text] [Related]

  • 18. Towards optimal multi-channel EMG electrode configurations in muscle force estimation: a high density EMG study.
    Staudenmann D, Kingma I, Stegeman DF, van Dieën JH.
    J Electromyogr Kinesiol; 2005 Feb 18; 15(1):1-11. PubMed ID: 15642649
    [Abstract] [Full Text] [Related]

  • 19. Heterogeneity of muscle activation in relation to force direction: a multi-channel surface electromyography study on the triceps surae muscle.
    Staudenmann D, Kingma I, Daffertshofer A, Stegeman DF, van Dieën JH.
    J Electromyogr Kinesiol; 2009 Oct 18; 19(5):882-95. PubMed ID: 18556216
    [Abstract] [Full Text] [Related]

  • 20. Predicting maximum eccentric strength from surface EMG measurements.
    Pain MT, Forrester SE.
    J Biomech; 2009 Aug 07; 42(11):1598-603. PubMed ID: 19464688
    [Abstract] [Full Text] [Related]

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