Modeling And Analysis Of Bioelectrical Impedance Spectrum Of Elbow Joint Based On Deep Learning

Elbow stiffness is a frequently occurring disease in clinic.Although orthosis has a significant therapeutic effect on it,because the elbow covers a variety of tissues such as pulse,blood and muscle,and there are significant differences in different tissue physical models,its biological information collection and analysis mechanism has not been established.Aiming at this problem,based on the combination of bioelectrical impedance spectroscopy and neural network,this paper uses the improved bis multi frequency synchronous fast analysis algorithm based on correlation detection algorithm to model and analyze the bioelectrical information in the rehabilitation process of patients with elbow stiffness.The completed work is as follows:(1)The research status of elbow rehabilitation and medical information detection is deeply investigated and studied.Taking the improved signal as the excitation source model for measuring bioelectrical impedance,a set of measurement and acquisition system based on instantaneous scanning is designed,and a set of improved bis multi frequency synchronous fast analysis algorithm based on correlation detection algorithm is established.(2)Actively improve the traditional Cole Cole and wavelet transform models,and make full use of MATLAB to carry out simulation experiments,so as to realize the objective verification of the practicability and effectiveness of relevant algorithms.(3)Through the improved cole-cole and wavelet transform model,and fully combined with the partial least square method,the relevant experimental data are processed and analyzed to obtain the time joint bioelectrical impedance spectrum data.BP neural network is used for training,the training results are obtained,and the data are used to analyze the pathological state of patients’ elbow joint.(4)The design and production of the bioelectrical impedance signal acquisition system and the elbow orthopedic device based on independent intellectual property rights completed the real-time monitoring and data storage of the patient’s bioelectrical impedance of the joint,with high efficiency and convenience.With the integration and development of biotechnology and artificial intelligence,modeling and analysis of bioelectrical information using deep learning is an interdisciplinary research hotspot.This paper uses deep learning to model bioelectric information,which can provide theoretical support and algorithm support for the research and development of elbow stiffness precision medical system.