A human motion prediction algorithm for Non-binding Lower Extremity Exoskeleton

This paper introduces a novel approach to predict human motion for the Non-binding Lower Extremity Exoskeleton (NBLEX). Most of the exoskeletons must be attached to the pilot, which exists potential security problems. In order to solve these problems, the NBLEX is studied and designed to free pilots from the exoskeletons. Rather than applying Electromyography (EMG) and Ground Reaction Force (GFR) signals to predict human motion in the binding exoskeleton, the non-binding exoskeleton robot collect the Inertial Measurement Unit (IMU) signals of the pilot. Seven basic motions are studied, each motion is divided into four phases except the standing-still motion which only has one motion phase. The human motion prediction algorithm adopts Support Vector Machine (SVM) to classify human motion phases and Hidden Markov Model (HMM) to predict human motion. The experimental data demonstrate the effectiveness of the proposed algorithm.