Neuromusculoskeletal Modeling: Estimation of Muscle Forces and Joint Moments and Movements from Measurements of Neural Command

Abstract

This paper provides an overview of forward dynamic neuromusculoskeletal modeling. The aim of such models is to estimate or predict muscle forces, joint moments, and/or joint kinematics from neural signals. This is a four-step process. In the first step, muscle activation dynamics govern the transformation from the neural signal to a measure of muscle activation-a time varying parameter between 0 and 1. In the second step, muscle contraction dynamics characterize how muscle activations are transformed into muscle forces. The third step requires a model of the musculoskeletal geometry to transform muscle forces to joint moments. Finally, the equations of motion allow joint moments to be transformed into joint movements. Each step involves complex nonlinear relationships. The focus of this paper is on the details involved in the first two steps, since these are the most challenging to the biomechanician. The global process is then explained through applications to the study of predicting isometric elbow moments and dynamic knee kinetics. Keywords Hill model; EMG; tendon; musculotendon complex; pennation angleThe eight-syllable term neuromusculoskeletal in the title of this article simply means that we will be modeling the movements produced by the muscular and skeletal systems as controlled by the nervous system. Neuromusculoskeletal modeling is important for studying functional electrical stimulation of paralyzed muscles, for designing prototypes of myoelectrically controlled limbs, and for general study of how the nervous system controls limb movements in both unimpaired people and those with pathologies such as spasticity induced by stroke or cerebral palsy.There are two fundamentally different approaches to studying the biomechanics of human movement: forward dynamics and inverse dynamics. Either approach can be used to determine joint kinetics (e.g., estimate joint moments during movements) and it is important that the differences between them are understood.NIH Public Access

Can pennation angles be predicted from EMGs for the primary ankle plantar and dorsiflexors during isometric contractions?

“…Contractile effort is reflected in the magnitude of the electromyogram (Buchanan et al, 2004), and therefore the EMG signal may be a predictor of fiber length and pennation angle change. The overarching finding of our study was that the relationship between EMG and pennation angle was fairly linear and statistically significant for all muscles tested (p < 0.05 ) when pennation angle at rest and MVC were included in the analysis.…”

Non-collision injuries in urban buses—Strategies for prevention

“…The main finger flexor muscles (flexor digitorum profundus and flexor digitorum superficialis) were combined into one single representative Hill type muscle with cross-sectional area and length derived from Lieber et al (1992). The maximum active muscle stress (86N/cm 2 ) reported by Buchanan et al (2004) was used.…”

A continuum model for skeletal muscle contraction at homogeneous finite deformations

“…This is often done by taking the developed force F to be the product of the isometric force F 0 and some experimentally motivated functions. For example, in a quick-release experiments, one may choose the normalized functions to be f (L) and g(V ) (both in the range [0,1]) describing the dependence on length L and velocity V , respectively, see, e.g., Buchanan et al (2004), Johansson et al (2000) and Liang et al (2006). These functions are, more or less, arbitrary which makes the method both flexible and simple, but also introduces some weaknesses.…”