Analysis of Bioelectrical Impedance Spectrum for Elbow Stiffness Based on Hilbert–Huang Transform

Author:

Gao Guodong1,Zhang Ping2ORCID,Xu Bin1,Zhang Xiaogang1,Yang QuanZeng1,Wang Rong1,Han ShuHuan2,Quan Zhen1

Affiliation:

1. Department of Spinal Surgery, Affiliated Hospital of Gansu University of Chinese Medicine, Lanzhou, Gansu 730000, China

2. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730050, China

Abstract

With the advent of posttraumatic elbow rehabilitation, prevention of elbow stiffness has become a key part of the development of sports medicine. In order to clarify the time point of joint movement after internal fixation to the elbow and to provide a mechanical model for individualized diagnosis. This paper uses electromagnetic wave detection technology to quickly detect the bioelectrical impedance signal of the patient's lesion location, then passes the message to the upper control system for processing, summarizes the improved Hilbert–Huang transform to deep learning, and deep learning algorithms and computer technology are used to mine the bioelectrical impedance signal of the elbow joint. The simulation and human experiment results show that bioelectrical impedance signals can clarify the pathogenesis of elbow joint stiffness and the relationship between rehabilitation treatment time and duration. It has the advantages of low cost, high fitting accuracy, strong robustness, and noninvasiveness.

Funder

National Science Foundation of China

Publisher

Hindawi Limited

Subject

Radiology, Nuclear Medicine and imaging

Reference20 articles.

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