Feasibility of using EMG driven neuromusculoskeletal model for prediction of dynamic movement of the elbow

Koo, Terry K.; Mak, Arthur F. T.

doi:10.1016/j.jelekin.2004.06.007

Cited by 107 publications

(51 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Muscle activations can be prescribed in an educated manner by directly incor porating EMG data into an EMG-driven forward dynam ics model, as pioneered by Hof and van den Berg (1981). The approach was also used to investigate elbow motion (Koo and Mak, 2005) and knee movements during the swing phase of walking (Piazza and Delp, 1996) and a step-up task (Piazza and Delp, 2001). The analysis is com monly performed by prescribing the trajectory of some joint angles, e.g.…”

Section: Alternative Strategiesmentioning

confidence: 99%

Model-based estimation of muscle forces exerted during movements

Erdemir

McLean

Herzog

et al. 2007

Clinical Biomechanics

727

543

View full text Add to dashboard Cite

Section: Alternative Strategiesmentioning

confidence: 99%

Model-based estimation of muscle forces exerted during movements

Erdemir

McLean

Herzog

et al. 2007

Clinical Biomechanics

727

543

View full text Add to dashboard Cite

“…The surface electromyogram (EMG) amplitude is often used to estimate the level of force produced by the muscle in conditions when it is not possible to measure the force directly (Wang & Buchanan 2002;Bogey et al 2005;Hoozemans & van Dieën 2005;Koo & Mak 2005;Staudenmann et al 2007;Gatti et al 2008). Such an application assumes a constant relation between surface EMG amplitude and muscle force.…”

Section: Introductionmentioning

confidence: 99%

Influence of fatigue on the simulated relation between the amplitude of the surface electromyogram and muscle force

Dideriksen

Farina

Enoka

2010

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

A linear relation between surface electromyogram (EMG) amplitude and muscle force is often assumed and used to estimate the contributions of selected muscles to various tasks. In the presence of muscle fatigue, however, changes in the properties of muscle fibre action potentials and motor unit twitch forces can alter the relation between surface EMG amplitude and force. A novel integrative model of motor neuron control and the generation of muscle fibre action potentials was used to simulate surface EMG signals and muscle force during three fatigue protocols. The change in the simulated relation between surface EMG amplitude and force depended on both the level of fatigue and the details of the fatiguing contraction. In general, surface EMG amplitude overestimated muscle force when fatigue was present. For example, surface EMG amplitudes corresponding to 60 per cent of the amplitude obtained at maximal force without fatigue corresponded to forces in the range 10-40% of the maximal force across three representative fatigue protocols. The results indicate that the surface EMG amplitude cannot be used to predict either the level of muscle activation or the magnitude of muscle force when the muscle exhibits any fatigue.

show abstract

“…Most muscle contractile parameters are difficult to measure in vivo, and are often estimated through a mathematical optimization procedure. 24,[33][34][35] Future modeling approaches that combine both direct measurements of muscle anatomic parameters and optimization procedures for muscle contractile parameters may further improve the accuracy and advance the application of an EMG-driven knee model.…”

mentioning

confidence: 99%

Greater muscle co‐contraction results in increased tibiofemoral compressive forces in females who have undergone anterior cruciate ligament reconstruction

Tsai

McLean

Colletti

et al. 2012

Journal Orthopaedic Research

114

View full text Add to dashboard Cite

Individuals who have undergone ACL reconstruction (ACLR) have been shown to have a higher risk of developing knee osteoarthritis (OA). The elevated risk of knee OA may be associated with increased tibiofemoral compressive forces. The primary purpose of this study was to examine whether females with ACLR demonstrate greater tibiofemoral compressive forces, as well as greater muscle co-contraction and decreased knee flexion during a single-leg drop-land task when compared to healthy females. Ten females with ACLR and 10 healthy females (control group) participated. Each participant underwent two data collection sessions: (1) MRI assessment and (2) biomechanical analysis (EMG, kinematics, and kinetics) during a single-leg drop-land task. Joint kinematics, EMG, and MRI-measured muscle volumes and patella tendon orientation were used as input variables into a MRI-based EMGdriven knee model to quantify the peak tibiofemoral compressive forces during landing. Peak tibiofemoral compressive forces were significantly higher in the ACLR group when compared to the control group (97.3 AE 8.0 vs. 88.8 AE 9.8 N Á kg À1 ). The ACLR group also demonstrated significantly greater muscle co-contraction as well as less knee flexion than the control group. Our findings support the premise that individuals with ACLR demonstrate increased tibiofemoral compression as well as greater muscle co-contraction and decreased knee flexion during a drop-land task. Future studies are needed to examine whether correcting abnormal neuromuscular strategies and reducing tibiofemoral compressive forces following ACLR can slow the progression of joint degeneration in this population. ß

show abstract

Feasibility of using EMG driven neuromusculoskeletal model for prediction of dynamic movement of the elbow

Cited by 107 publications

References 48 publications

Model-based estimation of muscle forces exerted during movements

Model-based estimation of muscle forces exerted during movements

Influence of fatigue on the simulated relation between the amplitude of the surface electromyogram and muscle force

Greater muscle co‐contraction results in increased tibiofemoral compressive forces in females who have undergone anterior cruciate ligament reconstruction

Contact Info

Product

Resources

About