Movement Reconstruction based on Motor Decomposition: Comparing Minimum Angular Jerk and Principal Component Analysis

Human movement science can inspire the studies in the fields of robotics and rehabilitation. In this study, based on Principal Component Analysis (PCA) applied to the experimental data of Sit to Stand (STS) transfer, the basic movement patterns which contribute to form the human motion trajectories are recognized. The STS transfer is decomposed into three phases of motion and six unique patterns are extracted from each phase using PCA. It is shown that the Central Nervous System applies a quasi minimum angular jerk policy to construct the joint trajectories of human movements in each phase of motion during STS. The results can help to plan human like trajectories for humanoids, rehabilitation robots or robot manipulators

کلیدواژه ها:

Principal Component Analysis ، Movement Elements ، Movement Patterns ، Sit-To-Stand