In this paper, we present a knee exoskeleton. Due to the complicated structure of the knee, an exoskeleton can limit the wearer's movement (e.g., when completely sitting down). To prevent this, the proposed exoskeleton is designed to move the ankle part prismatically, so the movement of the wearer is not limited. In addition, the developed exoskeleton could be worn on only one leg, but in this case, it is difficult to detect the intention because the relative relationship information of the two legs is unknown. For this purpose, the length between the knee center of rotation and the ankle (LBKA) was measured and used for intention detection. Using a physical sensor-an encoder and an LBKA sensor, the success rate of intention detection was 82.1%. By additionally using an electromyogram (EMG) sensor, the success rate of intention detection was increased to 92%, and the intention detection was also 27.1 ms faster on average.
Keywords: LBKA sensor; electromyogram (EMG); intention detection; knee exoskeleton; neural network; self-alignment; sensor fusion.