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

      retraction
      Contrast Media & Molecular Imaging
      Hindawi

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

          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.
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            Author and article information

            Contributors
            Journal
            Contrast Media Mol Imaging
            Contrast Media Mol Imaging
            CMMI
            Contrast Media & Molecular Imaging
            Hindawi
            1555-4309
            1555-4317
            2023
            26 July 2023
            26 July 2023
            : 2023
            : 9854181
            Affiliations
            Article
            10.1155/2023/9854181
            10397504
            69c0a9fb-8b2a-43cb-adce-c0b84e692fe3
            Copyright © 2023 Contrast Media & Molecular Imaging.

            This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            History
            : 25 July 2023
            : 25 July 2023
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