Research On Human Lower-Limb Motion Information Acquisition Technology Based On EMG

The human body maybe lost movement ability because of various subjective and objective limits. It not only affects the patients' psychological and physical state but also brings complex social problems. How to help them live independently has become very important nowadays.The concept of intelligent limb-assisted system aims at enhancing human movement capabilities and retaining the flexibility and feeling for direct operation at the same time. So how to obtain the limb's information effectively and precisely in real-time becomes urgent at present. EMG signals can directly reflect human muscles' function, based on that the dissertation mainly concentrates on two important contents. One is how to calculate muscle force and joint torques, and the other is how to recognize and predict the human motions.The main contents of this dissertation are shown as following:1. Summarized the tendency and methods for acquiring motion information at home and abroad. The advantages and disadvantages were pointed out. Narrated the main research contents and research methods for this thesis.2. The relationships between different lower-limb motion modes and EMG signals were analyzed through experiments. Standing up, going up and down stairs and walking were performed as the daily lower-limb motion in the experiment. The angle of each joint was measured by motion capture system and the activity levels of muscles were accessed by the muscle EMG signals. The results showed that different lower-limb motions had different muscle excitation time and excitation grade. It provided a practical basis for the following study.3. The recognition technology of lower-limb motion modes was studied based on Multi-Class SVM. First of all, the aims and difficulties of mode recognition on lower-limb motion based on EMG signals were expounded. Secondly, the analysis on EMG characteristics extraction has been done and an eigenvector space of mode recognition was built. On the other hand, developed an improved algorithm based on Multi-Class SVM. The results of mode recognition experiments showed this method could effectively resolve the lower-limb motion identifications in real-time.4. The muscle force and the joints torque prediction technique have been researched based on EMG Firstly, current application using EMG as a method for muscle force and joint torque calculation was analyzed. Then the benefits on muscles force and joint torque calculation based on single muscles stimulated were pointed out. Secondly, this research established a human body mechanics model based on the muscle physiological model, skeletal muscle model and multi-body dynamic model. Then the prediction model of the muscles force and joint torque was advanced. At last, the experiment results validated the model's availability.5. A prototype system was established to obtain motion information. Then the function of standing-up-assisted seat for the aged was analyzed and evaluated. It verified the feasibility and validity of theory, methods and techniques in this dissertation.