In this paper we use motion capture technology together with an electromyography (EMG) driven musculoskeletal model of the knee joint to predict muscle behavior during human dynamic movements. We propose a muscle model based on infinitely-stiff tendons and show this allows speeding up 250 times the computation of muscle force and the resulting joint moment calculation with no loss of accuracy with respect to the previously developed elastic tendon model. We then integrate our previously developed method for the estimation of 3D musculotendon kinematics in the proposed EMG-driven model. This new code enabled the creation of a stand-alone EMG-driven model that was implemented and run on an embedded system for applications in assistive technologies such as myoelectrically controlled prostheses and orthoses.
Modeling the Human Knee for Assistive Technologies
SARTORI, MASSIMO;REGGIANI, MONICA;PAGELLO, ENRICO;
2012
Abstract
In this paper we use motion capture technology together with an electromyography (EMG) driven musculoskeletal model of the knee joint to predict muscle behavior during human dynamic movements. We propose a muscle model based on infinitely-stiff tendons and show this allows speeding up 250 times the computation of muscle force and the resulting joint moment calculation with no loss of accuracy with respect to the previously developed elastic tendon model. We then integrate our previously developed method for the estimation of 3D musculotendon kinematics in the proposed EMG-driven model. This new code enabled the creation of a stand-alone EMG-driven model that was implemented and run on an embedded system for applications in assistive technologies such as myoelectrically controlled prostheses and orthoses.Pubblicazioni consigliate
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