Control of A Lower Limb Exoskeleton Robot by Upper Limb sEMG Signal

Abstract

In this paper, a lower limb exoskeleton robot based on upper limb sEMG signal controlledby designed for patients with lower limb functional injury in the middle and late stage of rehabilitation. It realized the patient's active and random control when wearing the lower limb exoskeleton for rehabilitation training. It solved the problem that the lower limb sEMG signal strength of patients with mobility difficulties leads to low acquisition accuracy, and the lower limb space of patients with wearing exoskeleton robot was compacted, which was inconvenient to collect sEMG signal. In this paper, three kinds of gait, which are static, normal walking and high leg lifting to avoid obstacles, are preliminarily formulated, and controlled by three different upper arm movements. This paper first introduced the research status at home and abroad. Then the principle and characteristics of sEMG signal are studied. Then the surface EMG signal was preprocessed and features were extracted, and the Angle prediction model was established by BP neural network. Finally, it is analyzed and verified by our experimental platform.