What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting

Abstract

How does the central nervous system control the body posture during various tasks despite a redundancy? It's a well-known question existed in such fields of study as biomechanics and bioengineering. Some techniques based on muscle and torques synergies are presented to study the function which Central Nervous System uses to addresses the kinetic redundancy in musculoskeletal system. The human body with its whole numerous joints considered as a hyper redundant structure which caused to be seemed that it is impossible for CNS to control and signal such system. To solve the kinematic redundancy in previous studies it is hypothesize that CNS functions as an optimizer, such of that are the task-based algorithms which search to find optimal solution for each specific task. In this research a new objective function based on ankle torques during movement is implemented to guarantee the stability of motion. A 2D 5DOF biomechatronical model of human body is subjected to lifting task simulation. The simulation process implements inverse dynamics as major constraint to consider the dynamics of motion for predicted postures. In the previous optimization-based techniques which are used to simulate the human movements, the motion stability was guaranteed by a nonlinear inequality constraint which restricts the total moment arm of the links to an upper and lower boundary. In this method, there is no need to use this constraint. The results show that the simulated postures are normal and the predicted motion is performed completely balanced.