Verification of the knee exoskeleton controller using novel gait phase detection method

Gait motion is the essential function for human being. Some diseases make it difficult for people to walk. Walking assist robot has been developed to assist gait motion for disabled people. Knee Exoskeleton is one of the walking assist robots. Knee Exoskeleton generates the assist torque for knee flexion or knee extension. The direction of the assist torque is controlled by the gait phase detection method. However, the conventional robot interferes with human intention because it generates flexion torque consistently in stance phase. In early stance phase, the user wants assist torque to support knee extension, but he wants knee flexion assist torque in late stance phase. The conventional controller does not detect late stance phase. In the previous study of the author, the novel gait phase detection algorithm is proposed to distinguish late stance phase. In this research, the novel algorithm is introduced for the proposed controller. A subject walks on the treadmill while wearing the knee exoskeleton. In the experiment, the exoskeleton is controlled by the conventional controller and the proposed controller. EMG of the popliteal muscle during gait motion is analyzed to evaluate whether the proposed controller succeeds to prevent interference with user's intention. Through the experiment, it is verified that the proposed controller succeeds to decrease the EMG of knee muscle by distinguishing early stance phase and late stance phase.