Knee Joint Angle Prediction Based on Gait Synergy Mechanism

Gait trajectory generation plays a pivotal role in designing the rehabilitative lower limb exoskeleton. The exoskeleton can generate personalized gait trajectories for different patients due to the gait synergy mechanism of human lower limbs. A lower limb gait prediction model is constructed based on complementary limb motion estimation (CLME). The model inputs the angle and angular velocity of the hip joint and outputs the angle of the knee joint of the same limb. Principal component analysis (PCA) and continuous relative phase (CRP) are utilized to analyze the synergy mechanism in a single lower limb. The influencing factors for prediction have been determined by examining the collaborative mechanisms among different participants. The experimental results demonstrate that the PCA-based CLME method excels at predicting knee joint angle and offers a straightforward explanation for the gait synergy mechanism.