Research On Diagnosis And Prediction Model Of Elbow Joint Contracture Based On The Combination Of BIS And GRNN Network

The elbow joint is prone to stiffness and adhesion after trauma or surgery.High-energy trauma can easily lead to loss of mobility of the elbow joint.Mild trauma can also cause stiffness in the elbow joint.In recent years,despite the remarkable progress made in the treatment of trauma to the elbow joint and surrounding tissues,postoperative elbow joint contractures are still very common.The improved elbow orthosis can provide a portable rehabilitation environment for the elbow joint after the operation,which is not affected by the environment,can be used for rehabilitation exercises.Bioimpedance spectroscopy(BIS)can quickly and accurately obtain mechanism information through the analysis of bioelectric signals,and has the characteristics of high speed,portability,and non-invasiveness.Therefore,this paper proposes a technical solution for elbow joint orthosis based on the combination of bioelectrical impedance spectros copy and GRNN neural network.The specific research work is as follows:(1)The research status of elbow joint rehabilitation and medical information detection was investigated,and an improved elbow joint orthosis was proposed and designed as the experimental platform of this article.(2)The traditional Cole-Cole model and VMD-HHT model are improved,and the simulation is carried out through Matlab to verify the effectiveness and practicability of the algorithm.(3)A feedback type elbow orthosis based on the combination of traditional elbow orthosis mechanical structure and electrical impedance signal acquisition hardware is designed,which realizes the real-time analysis of elbow orthosis to the patient’s elbow joint recovery pathological condition and contracture,and Based on the analysis results,the adjustment of the force applied by the elbow joint orthosis is realized.(4)A feedback type elbow joint control system based on GRNN network is proposed,which realizes the control strategy of converting the patient’s elbow joint pathological information into elbow joint orthosis control information.(5)The data obtained in the experiment were processed by the improved Cole-Cole model,partial least squares method,and improved VMD-HHT model.As the elbow joint continues to heal,the internal changes are the first to produce a large amount of extracellular fluid.And the conclusion that the wound can be healed through cell division.And input the information into the GRNN network for training,and finally adjust the force applied by the elbow joint orthosis to the patient’s elbow joint through the training results,and achieve good results.This article demonstrates the feasibility of bioimpedance spectroscopy(BIS)on the elbow joint and the feasibility of GRNN neural network to control the elbow joint orthosis.It provides a theoretical basis for the follow-up research on pathological signals of the elbow joint and the development of portable elbow joint rehabilitation equipment.