基于振动机械图的3D肌肉网络
C Sebastian Mancero Castillo1, S Farokh Atashzar2, Ravi Vaidyanathan1,3
1Department of Mechanical Engineering, Imperial College London, London, United Kingdom.
Journal of neural engineering
|October 9, 2023
概括
本研究介绍了使用振动机械图 (vMMG) 分析肌肉协调的3D肌肉网络. 这种新的方法揭示了手势期间显著的肌肉合,证明了vMMG.
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.
- 生物力学 生物力学
背景情况:
- 肌肉网络建模对于理解运动任务中的协同控制至关重要.
- 肌肉间连贯性 (IMC) 有助于确定神经肌肉控制中的同步.
- 电肌图 (EMG) 在空间和光纤信息方面的局限性需要先进的技术.
研究的目的:
- 通过振动机械学 (vMMG) 和IMC分析引入和评估三维 (3D) 肌肉网络.
- 评估跨频段和纤维方向的功能性肌肉共调.
- 确定基于vMMG的网络对手势分类和对传感器-皮肤接触力强度的实用性.
主要方法:
- 收集了从20个实验对象的vMMG数据,这些实验对象使用加速度计腕带执行手势.
- 从四个表面肌肉的IMC分解成三个频段,使用矩阵因子分解.
- 分析了vMMG网络对不同传感器皮肤接触力的反应.
主要成果:
- 确定了明显的拓差异和肌肉对之间的显著连贯合 (高达57%),根据频段,手势和方向变化.
- 没有发现随着接触力增加而信号强度的统计下降.
- 已证明基于vMMG的网络模型对组织压缩的变化具有强度.
结论:
- vMMG是用于肌肉连接分析的可行工具.
- IMC为手势分类提供了一个新的功能空间.
- 3D vMMG 肌肉网络模型为研究协同肌肉激活提供了新的基础,特别是在非临床环境中.
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