Department of Electric and Electronic Engineering, Public University of Navarra, Pamplona, Navarra, Spain.
Med Biol Eng Comput. 2010 Sep;48(9):875-86. doi: 10.1007/s11517-010-0642-x. Epub 2010 Jun 10.
The aim of this study was to develop a muscle architecture model able to account for the observed distributions of innervation ratios and fiber densities of different types of motor units in a muscle. A model algorithm is proposed and mathematically analyzed in order to obtain an inverse procedure that allows, by modification of input parameters, control over the output distributions of motor unit fiber densities. The model's performance was tested with independent data from a glycogen depletion study of the medial gastrocnemius of the rat. Results show that the model accurately reproduces the observed physiological distributions of innervation ratios and fiber densities and their relationships. The reliability and accuracy of the new muscle architecture model developed here can provide more accurate models for the simulation of different electromyographic signals.
本研究旨在开发一种肌肉结构模型,使其能够解释在肌肉中观察到的不同类型运动单位的神经支配比例和纤维密度分布。提出了一种模型算法,并进行了数学分析,以获得一种逆过程,通过修改输入参数来控制运动单位纤维密度的输出分布。该模型的性能通过来自大鼠内侧比目鱼肌糖原耗竭研究的独立数据进行了测试。结果表明,该模型准确地再现了观察到的神经支配比例和纤维密度及其关系的生理分布。这里开发的新肌肉结构模型的可靠性和准确性可以为不同肌电图信号的模拟提供更准确的模型。