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The real human arm is a complex kinematics system. It works according to instructions calculated by a highly accurate method, and has a moving system working by deity manner. The design and simulation analysis of arm moving system model with 7-Degree of Freedom (DOF) are presented. The electromyography (EMG) signal is the activation signal for muscles in human arm and accordingly the arm will have a certain movement. The arm dynamic system in real environment simulation was implemented using the inverse kinematics problem (IKP) analytical solution. The computation time of this simulation is very fast and has the ability to include any real constrain. The finite recurrent back propagation neural network ( FRBP-NN ) is used with the simulated system for identification, classification, and human arm movements recognition with respect to a specific EMG signal. Virtual Reality Toolbox, which is interfaced with the Simulink MATLAB. Satisfactory results are obtained, which give the solution of the forward and inverse kinematic human arm and the usefulness of using FRBP-NN to recognize the movements of human arm.