Real-time mode recognition based assistive torque control of bionic knee exoskeleton for sit-to-stand and stand-to-sit transitions

Abstract

Assistive torque control is important for people who cannot fully accomplish sit-to-stand and stand-to-sit (STS) transitions. In this paper, we proposed a three-level control strategy for a bionic knee exoskeleton based on real-time STS transition recognition. Motion features were obtained from one potentiometer and two inertial measurement units integrated in the exoskeleton. A multi-class support vector classifier was utilized to infer the subject’s real-time motion intent. Twelve able-bodied subjects were recruited in experiments. Mean accuracy across subjects was 97.63%±0.01%. Once STS transition was detected, the proposed control system could add assistive torque in time to assist the subject to accomplish the transition.