Lower Limb Rehabilitation Training Evaluation Method Based On Gait Analysis

At present,due to the increasing number of elderly people in China,the number of stroke patients commonly seen in the elderly is also increasing.Rehabilitation training of patients after a stroke will significantly improve their impaired motor function.In the traditional lower limb rehabilitation training,one-to-one auxiliary training is needed.Now the number of rehabilitation doctors in China is seriously insufficient,the rehabilitation training process is boring,the patient’s training enthusiasm cannot be fully mobilized,and the data generated during the patient training process cannot be quantitatively evaluated.The application of virtual reality technology to lower limb rehabilitation training can stimulate the training interest of patients.Therefore,the paper proposes a lower limb rehabilitation training method based on gait analysis and an evaluation model suitable for the lower limb rehabilitation training method.The main contents of the thesis are as follows:To study the theory of rehabilitation medicine and the traditional method of lower limb rehabilitation training,combined with medical knowledge to analyze the virtual training needs of lower limb rehabilitation,analyze the structure and relationship of the whole lower limb rehabilitation training equipment,select suitable sensors.According to the characteristics and laws of human gait cycle and the human skeleton data obtained by Kinect sensor,the paper designs a method to convert bone data into human gait parameters.The gait parameters transformed from the bone data is verified for accuracy,and the posture of the patient while walking is monitored and reminded.According to the different physical training environments of lower limb rehabilitation training and equipment design,a training method that requires the virtual footprints projected by the patient to calculate the degree of coincidence is proposed,and the lower limb rehabilitation training task with the target task is planned,which will be performed by Kinect.The gait parameters from the bone data is reflected in the training,Let the patient and the physician intuitively understand the current training state.The thesis combines the network analysis method with the grey system theory and the fuzzy synthesis method.According to the factors in the training method that affectthe training effect,the network analysis method is used to establish the evaluation index system of the patient training effect and the weight of each index.Then,the gray evaluation matrix is constructed by the grey system theory,and finally the fuzzy comprehensive evaluation method is used to establish the evaluation calculation model..In order to verify the lower limb rehabilitation training method and evaluation model proposed in the thesis,Designed and developed a prototype system for lower limb rehabilitation training.Through the prototype system,the patient can perform lower limb rehabilitation training,and the data generated during the training process can be objectively evaluated by the rehabilitation training evaluation model.