Agent-based Modeling and Simulation of Human Muscle For Development of Human Gait Analyzer Application
CoRR(2022)
摘要
Despite the fact that only a small portion of muscles are affected in motion
disease and disorders, medical therapies do not distinguish between healthy and
unhealthy muscles. In this paper, a method is devised in order to calculate the
neural stimuli of the lower body during gait cycle and check if any group of
muscles are not acting properly. For this reason, an agent-based model of human
muscle is proposed. The agent is able to convert neural stimuli to force
generated by the muscle and vice versa. It can be used in many researches
including medical education and research and prosthesis development. Then,
Boots algorithm is designed based on a biomechanical model of human lower body
to do a reverse dynamics of human motion by computing the forces generated by
each muscle group. Using the agent-driven model of human muscle and boots
algorithm, a user-friendly application is developed which can calculate the
number of neural stimuli received by each muscle during gait cycle. The
application can be used by clinical experts to distinguish between healthy and
unhealthy muscles.
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