Research On The Tactile And Slippery Perception And Control Of The Bionic Myoelectric Prosthetic Hand

As an important rehabilitation device,myoelectric prostheses can help patients with amputated limbs to recover the function of their limbs,and guarantee the basic working and living ability.Intelligent prosthetics has become an important goal of scientific research,and an important factor in evaluating the level of national rehabilitation development.However,most of the myoelectric prosthetic hands on the market today are threshold-controlled functional prostheses.Their control systems are simple and poorly flexible.They only have motion pattern recognition and can only perform simple actions.They lack the perception ability,and the grip is completely relying on the visual feedback of the user with the low safety performance.Aiming at the problems in the current research on artificial hands,this paper focuses on the multi-sensing control of myoelectric prostheses,and proposes an electromyographic prosthetic hand control scheme that integrates pattern recognition and multi-sensing functions.With PSo C4 as the main controller,an experimental platform is set up through software and hardware collaborative design.An EMG signal acquisition system was designed to complete the acquisition of EMG signals from the specified muscle.Select specific eigenvalues in the time and frequency domains,use the support vector machine algorithm based on particle swarm optimization to classify hand movements,and control the electromyography artificial hand to perform corresponding actions.In the research of the multi-sensing prosthetic hand function,soft hardness sensor and slip sensor are designed,and a new method for judging the hardness and slip perception of objects is proposed.Introduced fuzzy logic control,so that when the prosthetic hand grasps the object,it can load the appropriate grip force according to the hardness and sliding degree to realize the adaptive grip force.In order to verify the effectiveness of the control system,PSO-SVM prosthetic hand motion pattern recognition experiments and multi-perceptual feedback-based prosthetic hand grip control experiments were designed to achieve the expected control effect.