Research And Design Of Upper Limb Active Rehabilitation Method Based On Bilateral Synergy

Hemiplegia is a common sequelae of cerebral apoplexy,but can improve muscle capacity by training repeatedly over a long period of time.At present,the common upper limb assisted movement in the rehabilitation department is assisted by the rehabilitation therapist,but this recovery mode is too inefficient.In order to optimize the allocation of medical resources,a few hospitals have also introduced upper limb rehabilitation robots.Upper limb rehabilitation robots can help patients to do some stable and effective exercise training,but they always adopt the passive movement in a specific mode,which lacks the extraction and application of patients’ active movement consciousness.Therefore,based on the existed upper limb rehabilitation robot technology,we proposed an active upper limb rehabilitation method based on bilateral coordination.Which included the mirror principle,the sense technology and virtual reality technology to complete the upper limb rehabilitation system with motor and nerve recovery functions.Based on the theory of mirror rehabilitation and neural remodeling,combined with the design method of upper limb rehabilitation robot and virtual environment.This paper will introduce an active upper limb rehabilitation system that extracts the posture information of the healthy side from hemiplegia patients to assist the movement of another side.This system will take advantage of unilateral dyskinesia in hemiplegia to enhance the patient’s sense of autonomy in it.We generally introduce the biological basis of the whole upper limb active rehabilitation method,and divide the upper limb rehabilitation system into three parts: attitude information acquisition module,upper limb rehabilitation robot and virtual environment.The attitude information acquisition module uses the inertial sensor to collect the healthy arm and send it wirelessly.The upper limb rehabilitation robot receives and processes the information then applies it to the motion control.Virtual reality is used to create simulated worlds for training and entertainment,as well as to provide visual stimulation and corresponding human-computer interaction.Based on the system framework,we study the data transmission and motion control algorithm.We used a nine-axis inertial sensor with the algorithm to collect body information,transmit it by Wi-Fi,and finally analyze it through the frame rate.We compared various kinematics control algorithms such as classical PID and fuzzy control in the experiment of bilateral cooperative motion control.And finally chose the PID control algorithm based on RBF neural network parameter optimization,so as to improve the real-time performance of bilateral motion and the stability of the system.Through the test of data collection,it is confirmed that the system meets the needs of active rehabilitation and achieves the predetermined goal of the research.