Feasibility Study of Upper Limb Control Method Based On EMG-Angle Relation

Abstract

The method of inferring the human upper limb angles basis on EMG signals with the use of fuzzy logic neural network is discussed. The planar motion in sagittal plane is taken into account, and two EMG signals are analyzed. An artificial neural network with fuzzy logic is used to process EMG signals. The network predicts angular trajectories. On the basis of the difference between the current and the intended angular position, the driving torques are determined using simplified dynamic model. To verify the method, the real and predicted angles are compared. The difference between the torques evaluated using predicted angular trajectories and simplified dynamics, and the torques delivered by the OpenSim simulator using the true data is also studied. Obtained results confirm the correctness of the concept and its usefulness for controlling prostheses or exoskeletons.