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Updated: Sep 17, 2025

Semi-automated Analysis of Mouse Skeletal Muscle Morphology and Fiber-type Composition

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在不同的肌肉纤维组成和导电速度下,利用斯托克威尔变换特征对sEMG信号进行基于模型的分析

Venugopal G¹, Sidharth N², P A Karthick³

¹Department of Instrumentation and Control Engineering, N.S.S. College of Engineering (Affiliated to APJ Abdul Kalam Technological University, Kerala, India), Palakkad, Kerala, India.

Medical & biological engineering & computing

|July 3, 2025

概括

这项研究提出了一种模拟表面肌电图 (sEMG) 信号的新型模型,准确反映肌纤维类型差异,并通过实验数据验证它,以改善神经肌肉状况分析.

科学领域:

生物医学工程生物医学工程
神经科学是一个神经科学.
生理学生理学生理学

背景情况:

表面电肌图 (sEMG) 信号提供了关于肌肉激活和疲劳的见解.
了解肌肉纤维类型对sEMG的贡献对于准确的神经肌肉分析至关重要.
现有的sEMG模型需要改进以纳入动态生理参数.

研究的目的:

开发和验证一种用于模拟sEMG信号的新型计算模型.
研究肌肉纤维类型比例对sEMG特征的影响.
分析疲劳收缩期间sEMG信号的时间频率特性.

主要方法:

集成了现有的sEMG模型组件,修改了I型和II型电机单元的分布函数与时间变化的传导速度.
记录了来自 adductor pollicis (AP) 和 triceps brachii (TB) 肌肉的实验性sEMG,在最大自愿收缩 (MVC) 的30%,50%和70%到疲劳时.
使用斯托克威尔变换 (S变换) 进行时间频率分析,并计算单数值分解 (SVD) 特性 (最大 SV,能量,).

主要成果:

统计分析 (曼-惠特尼U测试) 显示了AP和TB肌肉之间提取的sEMG特征的显著差异.
布兰德-阿尔特曼分析显示,模拟和实验sEMG特征之间的高度一致.
时间频率分析表明,在疲劳期间,模拟和记录的信号都向较低频率转移.

结论:

拟议的sEMG模型准确模拟肌肉活动,并捕获纤维类型的特定特征.
该模型与实验数据的验证证实了其在研究神经肌肉状况方面的有用性.
这种方法为研究各种条件下的骨肌肉生理学提供了有价值的工具.

关键词:

附带器pollicisis 这是一个很好的方法.导电速度是指导的速度.肌肉纤维类型肌肉纤维类型斯托克威尔转换是什么意思表面电肌图 (sEMG) 是一种表面电肌图.三手臂 (Triceps brachii) 是一个大脑的支臂.sEMG模型的模型.

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