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基于表面肌电图分析的肢体骨折后固定所致废用性肌肉萎缩的无创定量评估

Non-Invasive and Quantitative Evaluation for Disuse Muscle Atrophy Caused by Immobilization After Limb Fracture Based on Surface Electromyography Analysis.

作者信息

Shi Lvgang, Hong Yuyin, Zhang Shun, Jin Hao, Wang Shengming, Feng Gang

机构信息

Polytechnic Institute, Zhejiang University, Hangzhou 310015, China.

College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou 310027, China.

出版信息

Diagnostics (Basel). 2024 Nov 29;14(23):2695. doi: 10.3390/diagnostics14232695.

DOI:10.3390/diagnostics14232695
PMID:39682606
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11640763/
Abstract

BACKGROUND

The clinical evaluation for disuse muscle atrophy usually depends on qualitative rating indicators with subjective judgments of doctors and some invasive measurement methods such as needle electromyography. Surface electromyography, as a non-invasive method, has been widely used in the detection of muscular and neurological diseases in recent years. In this paper, we explore how to evaluate disuse muscle atrophy based on surface electromyography; Methods: Firstly, we conducted rat experiments using hind-limb suspension to create a model of disuse muscle atrophy. Five groups of rats were suspended for 0, 3, 7, 14, and 21 days, respectively. We induced leg electromyography of rats through electrical stimulation and used fluorescence staining to obtain the fiber-type composition of rats' leg muscles. We obtained the best-fitting frequency bands of power spectrum density of surface electromyography for type I and type II fibers in rats' leg muscles by changing the frequency band boundaries. Secondly, we conducted tests on the human body and collected the electromyography of the atrophied muscles of the subjects over a period of 21 days. The changes in muscle fiber composition were evaluated using the frequency bands of power spectrum density obtained from rat experiments. The method was to evaluate the changes in type I fibers by the changes in the area of the best-fitting frequency band of type I fibers and to evaluate the changes in type II fibers by the changes in the area of the best-fitting frequency band of type II fibers.

RESULTS

The results of rat experiments showed that type I fibers best fit the frequency band of 20-330 Hz and type II fibers best fit the frequency band of 176-500 Hz. The results of human testing showed that the atrophy of the two types of fibers was consistent with the changes in the areas of the corresponding best-fitting frequency bands.

CONCLUSIONS

The test results demonstrate the feasibility of using surface electromyography to evaluate muscle fiber-type composition and subsequently assess muscle atrophy. Further research may contribute to the diagnosis and treatment of disuse muscle atrophy.

摘要

背景

废用性肌肉萎缩的临床评估通常依赖于医生主观判断的定性评级指标以及一些有创测量方法,如针极肌电图。表面肌电图作为一种无创方法,近年来已广泛应用于肌肉和神经疾病的检测。在本文中,我们探索如何基于表面肌电图评估废用性肌肉萎缩;方法:首先,我们进行大鼠实验,采用后肢悬吊法建立废用性肌肉萎缩模型。将五组大鼠分别悬吊0、3、7、14和21天。我们通过电刺激诱发大鼠腿部肌电图,并使用荧光染色获得大鼠腿部肌肉的纤维类型组成。通过改变频带边界,我们获得了大鼠腿部肌肉I型和II型纤维表面肌电图功率谱密度的最佳拟合频带。其次,我们对人体进行测试,并在21天内收集受试者萎缩肌肉的肌电图。使用从大鼠实验中获得的功率谱密度频带来评估肌肉纤维组成的变化。方法是通过I型纤维最佳拟合频带面积的变化来评估I型纤维的变化,通过II型纤维最佳拟合频带面积的变化来评估II型纤维的变化。

结果

大鼠实验结果表明,I型纤维最佳拟合20 - 330 Hz频带,II型纤维最佳拟合176 - 500 Hz频带。人体测试结果表明,两种类型纤维的萎缩与相应最佳拟合频带面积的变化一致。

结论

测试结果证明了使用表面肌电图评估肌肉纤维类型组成并随后评估肌肉萎缩的可行性。进一步的研究可能有助于废用性肌肉萎缩的诊断和治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/081c24555bf4/diagnostics-14-02695-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/8a07a28188d3/diagnostics-14-02695-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/034a4cc79e46/diagnostics-14-02695-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/471def561932/diagnostics-14-02695-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/263559d6be1d/diagnostics-14-02695-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/f8ef9573e73f/diagnostics-14-02695-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/876d90563dc7/diagnostics-14-02695-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/db1b6b6f2756/diagnostics-14-02695-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/a2f50c471155/diagnostics-14-02695-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/081c24555bf4/diagnostics-14-02695-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/8a07a28188d3/diagnostics-14-02695-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/034a4cc79e46/diagnostics-14-02695-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/471def561932/diagnostics-14-02695-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/263559d6be1d/diagnostics-14-02695-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/f8ef9573e73f/diagnostics-14-02695-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/876d90563dc7/diagnostics-14-02695-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/db1b6b6f2756/diagnostics-14-02695-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/a2f50c471155/diagnostics-14-02695-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a91b/11640763/081c24555bf4/diagnostics-14-02695-g009.jpg

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