EMG assisted optimization: a hybrid approach for estimating muscle forces in an indeterminate biomechanical model.
There are two basic approaches to estimate individual muscle forces acting on a joint, given the indeterminacy of moment balance equations: optimization and electromyography (EMG) assisted. Each approach is characterized by unique advantages and liabilities. With this in mind, a new hybrid method which combines the advantages of both of these traditional approaches, termed 'EMG assisted optimization' (EMGAO), was described. In this method, minimal adjustments are applied to the individual muscle forces estimated from EMG, so that all moment equilibrium equations are satisfied in three dimensions. The result is the best possible match between physiologically observed muscle activation patterns and the predicted forces, while satisfying the moment constraints about all three joint axes. Several forms of the objective function are discussed and their effect on individual muscle adjustments is illustrated in a simple two-dimensional example.
Department of Kinesiology, Faculty of Applied Health Sciences, University of Waterloo, Ontarco, Canada.
J
J
Cholewicki
S M
SM
McGill
D000465:Algorithms; D001696:Biomechanical Phenomena; D004576:Electromyography; D005544:Forecasting; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007596:Joints / Q000502:physiology; D008159:Lumbar Vertebrae / Q000502:physiology; D008954:Models, Biological; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D013314:Stress, Mechanical