Analysis of neuromuscular control in human arm

The central nervous system directs a large number of muscles to produce complex motor behaviors. By using Artificial neural networks (ANNs) where more number of hidden layers are used for learning a specific task, we propose a method to understand the representations of neuromuscular control in the central nervous system as representations of movement plans that are eventually executed by the spinal cord and muscles in the periphery. In this report, we provide our results in attempting to build a neural network that enables muscle activation implemented in OpenSim — a biomechanical software to simulate the right upper arm of a human body. It is expected that this project will provide fundamental insights into the neuromuscular control.