Implementation issues of EMG-based motion intention detection for exoskeletal robots

Abstract

Despite the advantages of electromyography (EMG), which can grasp intent before actual movement, there have not been many studies on the use of EMG in exoskeletons. In this paper, we conducted an experiment to analyze the characteristics of electromyography when EMG signals are used in exoskeleton robots. We integrated the advantages of EMG sensors and physical sensors to control exoskeleton robots using EMG signals and physical signals. The walking environment was defined using the surface electromyography (sEMG) signal and the physical signal to an accuracy of 88% or more. To compensate for the limitations of physical sensors, we used sEMG to distinguish changes in the load during walking. Moreover, sEMG signals and physical signals were used to distinguish external collisions and to identify other variables that could be distinguished. Finally, to examine the characteristics of muscular fatigue, which is a disadvantage when using electromyography, we conducted a muscle fatigue experiment in the lower limb and summarized how the EMG characteristics change in relation to the degree of force and the muscle fatigue.