What is it about?

This study deals with neuro-musculo-skeletal system modeling. The biomechanical behavior of this system can be modeled by mathematical equations which show how the central nervous system signals called EMGs are transformed to calcium ions in muscles, recognized as muscle activations, how the activations are transformed to the muscle forces and how the muscle forces are transformed to the torque which moves the body joint like a mechanical motor. Since there is more than one muscle at each joint of our body, it is not known how these muscle share force. This is a serious challenging for researches to find out how the muscle force sharing work in human body. Despite all the effort, there is not an absolute answer. The most well-known answer is that the muscles share the force in which the total forces of muscle is minimum, therefore our body does not need extra energy to move. If we accept this answer, many solutions can be presented. These solutions are mostly cost intensive. The runtime to find the solution (minimize total muscle forces) is very expensive and therefore not suitable. We tried to propose a mathematical method that decreases runtime considerably, so the neuro-musculo-skeletal system modeling can be applied for clinical purposes.

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Why is it important?

There are many different clinical applications need neuro-musculo-skeletal system analysis or modeling. The complication of this system prevents its wider use for clinical applications. We tried to present an effective method to model this system, therefore it can provide an appropriate platform to use neuro-musculo-skeletal system modeling for clinical applications.


Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations. This article also provides a better understanding of neuro-musculo-skeletal system for many students at our department.

seyed mohammadali rahmati
Amirkabir University of Technology

Read the Original

This page is a summary of: A Novel Optimization Framework to Improve the Computational Cost of Muscle Activation Prediction for a Neuromusculoskeletal System, Neural Computation, March 2019, The MIT Press,
DOI: 10.1162/neco_a_01167.
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