Research On Human-Machine Interface Of Mandibular Rehabilitation Robot

In recent years,the demands of the elderly and the disabled on personal support systems have been increasing,so man-machine interaction technology has become a hot research field.Because this device interacts directly with the user,the development of this human-machine interaction technology faces great challenges in design.An sEMG acquisition system was designed,and the sEMG of the masseter and the digastric and the vertical displacement of the incisal point were collected.The sEMG was processed in MATLAB,and the signal activation characteristic value was obtained.An sEMG-driven mandibular joint physiological model interface was developed to predict the continuous movement of the mandibular joints.The model was constructed based on anatomical data and some reasonable assumptions were made.The establishment of this physiological model of the mandibular joint opens up a new idea for the motion prediction of the joint system with complex small amplitude motion.The physiological model parameters were evaluated using a sensitivity calculation method to establish a relatively small subset of parameters for parameter tuning.The physiological model is simulated and verified in MATLAB,and the parameters in the physiological model are optimized by genetic algorithm.The simulation results show that the physiological model can effectively predict the movement of the mandible.A mandibular rehabilitation robot was designed and a virtual prototype was built in CREO.It can adjust the robot according to different sitting height,condylar position and mandible length,and can also adjust different gear positions according to the patient during different rehabilitation periods.The robot is fully functional and lightweight,and is convenient for patients with temporomandibular joint diseases.The man-machine interface designed can make the mandibular rehabilitation robot come from the main rehabilitation training according to the people's willingness to exercise,which effectively improve the training effect.Figure54;Table17;Reference 65...